Author name cluster

Michael Yu Wang

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43 papers

1 author row

ICRA Conference 2025 Conference Paper

Master Rules from Chaos: Learning to Reason, Plan, and Interact from Chaos for Tangram Assembly

Chao Zhao 0004
Chunli Jiang
Lifan Luo
Guanlan Zhang
Hongyu Yu
Michael Yu Wang
Qifeng Chen 0001

Tangram assembly, the art of human intelligence and manipulation dexterity, is a new challenge for robotics and reveals the limitations of state-of-the-arts. Here, we describe our initial exploration and highlight key problems in reasoning, planning, and manipulation for robotic tangram assembly. We present MRChaos (Master Rules from Chaos), a robust and general solution for learning assembly policies that can generalize to novel objects. In contrast to conventional methods based on prior geometric and kinematic models, MRChaos learns to assemble randomly generated objects through self-exploration in simulation without prior experience in assembling target objects. The reward signal is obtained from the visual observation change without manually designed models or annotations. MRChaos retains its robustness in assembling various novel tangram objects that have never been encountered during training, with only silhouette prompts. We show the potential of MRChaos in wider applications such as cutlery combinations. The presented work indicates that radical generalization in robotic assembly can be achieved by learning in much simpler domains. The code will be available https://robotll.github.io/MasterRulesFromChaos/.

IROS Conference 2024 Conference Paper

CompdVision: Combining Near-Field 3D Visual and Tactile Sensing Using a Compact Compound-Eye Imaging System

Lifan Luo
Boyang Zhang
Zhijie Peng
Yik Kin Cheung
Guanlan Zhang
Zhigang Li
Michael Yu Wang
Hongyu Yu

As automation technologies advance, the need for compact and multi-modal sensors in robotic applications is growing. To address this demand, we introduce CompdVision, a novel sensor that employs a compound-eye imaging system to combine near-field 3D visual and tactile sensing within a compact form factor. CompdVision utilizes two types of vision units to address diverse sensing needs, eliminating the need for complex modality conversion. Stereo units with far-focus lenses can see through the transparent elastomer for depth estimation beyond the contact surface. Simultaneously, tactile units with near-focus lenses track the movement of markers embedded in the elastomer to obtain contact deformation. Experimental results validate the sensor’s superior performance in 3D visual and tactile sensing, proving its capability for reliable external object depth estimation and precise measurement of tangential and normal contact forces. The dual modalities and compact design make the sensor a versatile tool for robotic manipulation.

IROS Conference 2024 Conference Paper

MOE: A Dense LiDAR MOving Event Dataset, Detection Benchmark and LeaderBoard

Zhiming Chen
Haozhe Fang
Jiapeng Chen
Michael Yu Wang
Hongyu Yu

Detecting moving events produced by moving objects is a crucial task in the realms of autonomous driving and mobile robots. Moving objects have the potential to create ghost artifacts in mapped environments and pose risks to autonomous navigation. LiDAR serves as a vital sensor for autonomous systems due to its ability to provide dense and precise range measurements. However, existing LiDAR datasets often lack sufficient discussion on the motion labeling of moving objects, containing only a limited representation of moving entities within a single scene. Furthermore, the methodologies for Moving Event Detection (MED) on LiDAR sensors have not been comprehensively explored or evaluated. To address these gaps, this study focuses on constructing a diverse LiDAR moving event dataset encompassing multiple scenes with a high density of moving objects. A thorough review of current MED techniques is conducted, followed by the establishment of a performance benchmark based on evaluating these methods using our dataset. Additionally, part sequences of the dataset are utilized to host an online MED competition, aimed at fostering collaboration within the research community and advancing related studies.

ICML Conference 2024 Conference Paper

RoboMP2: A Robotic Multimodal Perception-Planning Framework with Multimodal Large Language Models

Qi Lv 0001
Hao Li
Xiang Deng 0002
Rui Shao 0001
Michael Yu Wang
Liqiang Nie

Multimodal Large Language Models (MLLMs) have shown impressive reasoning abilities and general intelligence in various domains. It inspires researchers to train end-to-end MLLMs or utilize large models to generate policies with human-selected prompts for embodied agents. However, these methods exhibit limited generalization capabilities on unseen tasks or scenarios, and overlook the multimodal environment information which is critical for robots to make decisions. In this paper, we introduce a novel Robo tic M ultimodal P erception- P lanning ( RoboMP$^2$ ) framework for robotic manipulation which consists of a Goal-Conditioned Multimodal Preceptor (GCMP) and a Retrieval-Augmented Multimodal Planner (RAMP). Specially, GCMP captures environment states by employing a tailored MLLMs for embodied agents with the abilities of semantic reasoning and localization. RAMP utilizes coarse-to-fine retrieval method to find the $k$ most-relevant policies as in-context demonstrations to enhance the planner. Extensive experiments demonstrate the superiority of RoboMP$^2$ on both VIMA benchmark and real-world tasks, with around 10% improvement over the baselines.

IROS Conference 2024 Conference Paper

Stick Roller: Precise In-hand Stick Rolling with a Sample-Efficient Tactile Model

Yipai Du
Pokuang Zhou
Michael Yu Wang
Wenzhao Lian
Yu She

In-hand manipulation is challenging in robotics due to the intricate contact dynamics and high degrees of control freedom. Precise manipulation with high accuracy often requires tactile perception, which adds further complexity to the system. Despite the challenges in perception and control, the rolling stick problem is an essential and practical motion primitive with many demanding industrial applications. This work aims to learn the high-resolution tactile dynamics of the rolling stick. Specifically, we try manipulating a small stick using the Allegro hand equipped with the Digit vision-based tactile sensor. The learning framework includes an action filtering module, tactile perception module, and learning with uncertainty module, all designed to operate in low data regimes. With only 2. 3% amount of data and 5. 7% model complexity of previous similar work, our learned contact dynamics model achieves better grasp stability, sub-millimeter precision, and promising zero-shot generalizability across novel objects. The proposed framework demonstrates the potential for precise in-hand manipulation with tactile feedback on real hardware. The project source code is available at: https://github.com/duyipai/Allegro_Digit.A video presentation is available here.

ICRA Conference 2023 Conference Paper

Flipbot: Learning Continuous Paper Flipping via Coarse-to-Fine Exteroceptive-Proprioceptive Exploration

Chao Zhao 0004
Chunli Jiang
Junhao Cai
Michael Yu Wang
Hongyu Yu
Qifeng Chen 0001

This paper tackles the task of singulating and grasping paper-like deformable objects. We refer to such tasks as paper-flipping. In contrast to manipulating deformable objects that lack compression strength (such as shirts and ropes), minor variations in the physical properties of the paper-like deformable objects significantly impact the results, making manipulation highly challenging. Here, we present Flipbot, a novel solution for flipping paper-like deformable objects. Flipbot allows the robot to capture object physical properties by integrating exteroceptive and proprioceptive perceptions that are indispensable for manipulating deformable objects. Furthermore, by incorporating a proposed coarse-to-fine exploration process, the system is capable of learning the optimal control parameters for effective paper-flipping through proprioceptive and exteroceptive inputs. We deploy our method on a real-world robot with a soft gripper and learn in a self-supervised manner. The resulting policy demonstrates the effectiveness of Flipbot on paper-flipping tasks with various settings beyond the reach of prior studies, including but not limited to flipping pages throughout a book and emptying paper sheets in a box. The code is available here: https://robotll.github.io/Flipbot/.

ICRA Conference 2023 Conference Paper

Vision-based Six-Dimensional Peg-in-Hole for Practical Connector Insertion

Kun Zhang 0017
Chen Wang 0123
Hua Chen 0007
Jia Pan 0001
Michael Yu Wang
Wei Zhang 0013

We study six-dimensional (6D) perceptive peg-in-hole problem for practical connector insertion task in this paper. To enable the manipulator system to handle different types of pegs in complex environment, we develop a perceptive robotic assembly system that utilizes an in-hand RGB-D camera for peg-in-hole with multiple types of pegs. The proposed framework addresses the critical hole detection and pose estimation problem through combining the learning-based detection with model-based pose estimation strategies. By exploiting the structure of the peg-in-hole task, we consider a rectangle-shape based characterization for modeling the candidate socket. Such a characterization allows us to design simple learning-based methods to detect and estimate the 6D pose of the target socket that balances between processing speed and accuracy. To validate our method, we test the performance of the proposed perceptive peg-in-hole solution using a KUKA iiwa7 robotic arm to accomplish the socket insertion task with two types of practical sockets (RJ45/HDMI). Without the need of additional search, our method achieves an acceptable success rate in the connector insertion tasks. The results confirm the reliability of our method and show that our method is suitable for real world application.

ICRA Conference 2022 Conference Paper

SpecTac: A Visual-Tactile Dual-Modality Sensor Using UV Illumination

Qi Wang 0105
Yipai Du
Michael Yu Wang

Perceiving the dynamical environment both visually and tactilely is crucial for the survival of animals, and therefore, is considered of importance in robotics research. Recently, there has been an increasing interest in vision-based tactile sensors due to their high sensing resolution and robustness to environmental changes. However, almost all vision-based tactile sensors make only partial use of the camera, specifically, only when contact occurs, and stay idle at other times, which results in a waste of the camera information bandwidth. In this paper, we propose a new visual-tactile dual-modality sensor called SpecTac, which can visually inspect the environment and make tactile observations. The main novelty of the sensor is the use of ultraviolet (UV) LEDs and randomly distributed UV fluorescent markers. When the LEDs are on, those markers will be bright and can easily be distinguished and tracked from the background. Besides, by controlling the on and off of the UV LEDs, due to the switchable visibility of those markers, the sensor will switch between visual and tactile sensing mode. The qualities of tactile and visual perception are evaluated quantitatively by force estimation, visual triangulation and visual feature matching. By combining both modalities into one compact sensor, the information from the camera is better utilized, and it is hoped that the sensor will achieve more flexibility in the motion of the robot arm, especially in tasks where the workspace is narrow.

ICRA Conference 2021 Conference Paper

A Tactile Sensing Foot for Single Robot Leg Stabilization

Guanlan Zhang
Yipai Du
Yazhan Zhang
Michael Yu Wang

Tactile sensing on human feet is crucial for motion control, however, has not been explored in robotic counterparts. This work is dedicated to endowing tactile sensing to legged robot’s feet and showing that a single-legged robot can be stabilized with only tactile sensing signals from its foot. We propose a robot leg with a novel vision-based tactile sensing foot system and implement a processing algorithm to extract contact information for feedback control in stabilizing tasks. A pipeline to convert images of the foot skin into high-level contact information using a deep learning framework is presented. The leg was quantitatively evaluated in a stabilization task on a tilting surface to show that the tactile foot was able to estimate both the surface tilting angle and the foot poses. Feasibility and effectiveness of the tactile system were investigated qualitatively in comparison with conventional single-legged robotic systems using inertia measurement units (IMU). Experiments demon-strate the capability of vision-based tactile sensors in assisting legged robots to maintain stability on unknown terrains and the potential for regulating more complex motions for humanoid robots.

IROS Conference 2021 Conference Paper

Stereo Matching by Self-supervision of Multiscopic Vision

Weihao Yuan 0001
Yazhan Zhang
Bingkun Wu
Siyu Zhu 0001
Ping Tan 0002
Michael Yu Wang
Qifeng Chen 0001

Self-supervised learning for depth estimation possesses several advantages over supervised learning. The benefits of no need for ground-truth depth, online fine-tuning, and better generalization with unlimited data attract researchers to seek self-supervised solutions. In this work, we propose a new self-supervised framework for stereo matching utilizing multiple images captured at aligned camera positions. A cross photometric loss, an uncertainty-aware mutual-supervision loss, and a new smoothness loss are introduced to optimize the network in learning disparity maps end-to-end without ground-truth depth information. To train this framework, we build a new multiscopic dataset consisting of synthetic images rendered by 3D engines and real images captured by real cameras. After being trained with only the synthetic images, our network can perform well in unseen outdoor scenes. Our experiment shows that our model obtains better disparity maps than previous unsupervised methods on the KITTI dataset and is comparable to supervised methods when generalized to unseen data. Our source code and dataset are available at https://sites.google.com/view/multiscopic.

ICRA Conference 2021 Conference Paper

Viko: An Adaptive Gecko Gripper with Vision-based Tactile Sensor

Chohei Pang
Kinwing Mak
Yazhan Zhang
Yang Yang 0031
Yu Alexander Tse
Michael Yu Wang

Monitoring the state of contact is essential for robotic devices, especially grippers that implement geckoinspired adhesives where intimate contact is crucial for a firm attachment. However, due to the lack of deformable sensors, few have demonstrated tactile sensing for gecko grippers. We present Viko, an adaptive gecko gripper that utilizes vision-based tactile sensors to monitor contact state. The sensor provides high-resolution real-time measurements of contact area and shear force. Moreover, the sensor is adaptive, low-cost, and compact. We integrated gecko-inspired adhesives into the sensor surface without impeding its adaptiveness and performance. Using a robotic arm, we evaluate the performance of the gripper by a series of grasping test. The gripper has a maximum payload of 8N even at a low fingertip pitch angle of 30°. We also showcase the gripper’s ability to adjust fingertip pose for better contact using sensor feedback. Further, everyday object picking is presented as a demonstration of the gripper’s adaptiveness.

ICRA Conference 2020 Conference Paper

A Compact and Low-cost Robotic Manipulator Driven by Supercoiled Polymer Actuators

Yang Yang 0031
Zhicheng Liu
Yanhan Wang
Shuai Liu
Michael Yu Wang

The supercoiled polymer (SCP) actuator is a novel artificial muscle, which is manufactured by twisting and coiling polymer fibers. This new artificial muscle is soft, low-cost and shows good linearity. Being utilized as an actuator, the artificial muscle could generate significant mechanical power in a muscle-like form upon electrical activation by Joule heating. In this study, we adopt this new artificial muscle to actuate a novel designed robotic manipulator, which is composed of two parts. The first part is a robotic arm based on the inspiration of the musculoskeletal system. The arm is fabricated with two ball-and-socket joints as skeleton and SCP actuators as driven muscles. The second part is a Fin Ray Effect inspired soft gripper that can perform grasping tasks on fragile objects. The manipulator prototype is fabricated and experimental tests are conducted including both simple but effective control of the bio-inspired arm as well as characterization of the gripper. Lastly, a pick and place demonstration of a fragile fruit is performed utilizing the proposed manipulator. We envision that the bio-inspired robotic manipulator design driven by SCP actuators could potentially be used in other robotic applications.

IROS Conference 2020 Conference Paper

Multi-Object Rearrangement with Monte Carlo Tree Search: A Case Study on Planar Nonprehensile Sorting

Haoran Song
Joshua A. Haustein
Weihao Yuan 0001
Kaiyu Hang
Michael Yu Wang
Danica Kragic
Johannes A. Stork

In this work, we address a planar non-prehensile sorting task. Here, a robot needs to push many densely packed objects belonging to different classes into a configuration where these classes are clearly separated from each other. To achieve this, we propose to employ Monte Carlo tree search equipped with a task-specific heuristic function. We evaluate the algorithm on various simulated and real-world sorting tasks. We observe that the algorithm is capable of reliably sorting large numbers of convex and non-convex objects, as well as convex objects in the presence of immovable obstacles.

IROS Conference 2020 Conference Paper

Novel Design of a Soft Pump Driven by Super-Coiled Polymer Artificial Muscles

Yu Alexander Tse
Ki Wan Wong
Yang Yang 0031
Michael Yu Wang

The widespread use of fluidic actuation for soft robots creates a high demand for soft pumps and compressors. However, current off-the-shelf pumps are usually rigid, noisy, and cumbersome. As a result, it is hard to integrate most commercial pumps into soft robotic systems, which restricts the autonomy and portability of soft robots. This paper presents the novel design of a soft pump based on bellow structure and super-coiled polymer (SCP) artificial muscles. The pump is flexible, lightweight, modular, scalable, quiet, and low cost. The pumping mechanism and fabrication process of the proposed soft pump is demonstrated. A pump prototype is fabricated to verify the proposed design and characterize its performance. From the characterization results, the pump can reach an output flow rate of up to 54 ml/min and delivers pressure up to 2. 63 kPa. The pump has potential applications in untethered soft robots and wearable devices.

ICRA Conference 2020 Conference Paper

Parallel-motion Thick Origami Structure for Robotic Design

Shuai Liu
Huajie Wu
Yang Yang 0031
Michael Yu Wang

Structures with origami design enable objects to transform into various three-dimensional shapes. Traditionally origami structures are designed with zero-thickness flat paper sheets. However, the thickness and intersection of origami facets are non-negligible in most cases, uniquely when integrating origami design with robotic design because of the more efficient force transfer between thick plates compared with zero-thickness paper-sheets. Meanwhile, the single-layer-paper oriented initial design limited the shape transformation potential as multiple layer origami structures could conduct more variety of deformation. In this article, we are proposing a general design method of parallel-motion thick origami structures that could apply in robotic design like a parallel-motion gripper.

IROS Conference 2020 Conference Paper

Self-supervised Object Tracking with Cycle-consistent Siamese Networks

Weihao Yuan 0001
Michael Yu Wang
Qifeng Chen 0001

Self-supervised learning for visual object tracking possesses valuable advantages compared to supervised learning, such as the non-necessity of laborious human annotations and online training. In this work, we exploit an end-to-end Siamese network in a cycle-consistent self-supervised framework for object tracking. Self-supervision can be performed by taking advantage of the cycle consistency in the forward and backward tracking. To better leverage the end-to-end learning of deep networks, we propose to integrate a Siamese region proposal and mask regression network in our tracking framework so that a fast and more accurate tracker can be learned without the annotation of each frame. The experiments on the VOT dataset for visual object tracking and on the DAVIS dataset for video object segmentation propagation show that our method outperforms prior approaches on both tasks.

IROS Conference 2020 Conference Paper

Vacuum Driven Auxetic Switching Structure and Its Application on a Gripper and Quadruped

Shuai Liu
Sheeraz Athar
Michael Yu Wang

The properties and applications of auxetics have been widely explored in the past years. Through proper utilization of auxetic structures, designs with unprecedented mechanical and structural behaviors can be produced. Taking advantage of this, we present the development of novel and low-cost 3D structures inspired by a simple auxetic unit. The core part, which we call the body in this paper, is a 3D realization of 2D rotating squares. This body structure was formed by joining four similar structures through softer material at the vertices. A monolithic structure of this kind is accomplished through a custom-built multi-material 3D printer. The model works in a way that, when torque is applied along the face of the rotational squares, they tend to bend at the vertex of the softer material, and due to the connected-ness of the design, a proper opening and closing motion is achieved. To demonstrate the potential of this part as an important component for robots, two applications are presented: a soft gripper and a crawling robot. Vacuum-driven actuators move both the applications. The proposed gripper combines the benefits of two types of grippers whose fingers are placed parallel and equally spaced to each other, in a single design. This gripper is adaptable to the size of the object and can grasp objects with large and small cross- sections alike. A novel bending actuator, which is made of soft material and bends in curvature when vacuumed, provides the grasping nature of the gripper. Crawling robots, in addition to their versatile nature, provide a better interaction with humans. The designed crawling robot employs negative pressure-driven actuators to highlight linear and turning locomotion.

ICRA Conference 2019 Conference Paper

A Novel Variable Stiffness Actuator Based on Pneumatic Actuation and Supercoiled Polymer Artificial Muscles

Yang Yang 0031
Zicheng Kan
Yazhan Zhang
Yu Alexander Tse
Michael Yu Wang

This article describes an innovative design of variable stiffness soft actuator, which can potentially be utilized for manipulation and locomotion of soft robots. The new actuator is a combination of two types of actuations: soft pneumatic actuation and muscle-like supercoiled polymer (SCP) actuation. Soft pneumatic actuator has two roles: first is to generate bending motions and second is to increase the stiffness of the whole actuator together with SCP artificial muscles. SCP artificial muscles are exploited to generate pre-load to resist the whole actuator from (excessive) deformation when external load is applied. These two types of actuations are arranged antagonistically to realize stiffness tuning of the whole actuator. At a given bending position, stiffness of the actuator could be tuned by controlling the pressure inside the air chamber and the tension on the SCP artificial muscles. In experimental section, tests are conducted to characterize the applied SCP artificial muscles before they are applied to the proposed actuator. Afterwards, tests of proposed actuator are performed to examine its variable stiffness capability. From experimental results, the proposed actuator can achieve 3. 47 times stiffness variation ratio from 0. 0312 N/mm(40kPa air pressure and no SCP actuation) to 0. 1083 N/mm(82kPa air pressure and SCP actuation at 0. 143 W/cm) at the same position (bending angle of 56 degree). This study exhibits the potential of applying SCP artificial muscles to promote the performance of soft robots.

ICRA Conference 2019 Conference Paper

Reinforcement Learning in Topology-based Representation for Human Body Movement with Whole Arm Manipulation

Weihao Yuan 0001
Kaiyu Hang
Haoran Song
Danica Kragic
Michael Yu Wang
Johannes A. Stork

Moving a human body or a large and bulky object may require the strength of whole arm manipulation (WAM). This type of manipulation places the load on the robot's arms and relies on global properties of the interaction to succeed- rather than local contacts such as grasping or non-prehensile pushing. In this paper, we learn to generate motions that enable WAM for holding and transporting of humans in certain rescue or patient care scenarios. We model the task as a reinforcement learning problem in order to provide a robot behavior that can directly respond to external perturbation and human motion. For this, we represent global properties of the robot-human interaction with topology-based coordinates that are computed from arm and torso positions. These coordinates also allow transferring the learned policy to other body shapes and sizes. For training and evaluation, we simulate a dynamic sea rescue scenario and show in quantitative experiments that the policy can solve unseen scenarios with differently-shaped humans, floating humans, or with perception noise. Our qualitative experiments show the subsequent transporting after holding is achieved and we demonstrate that the policy can be directly transferred to a real world setting.

ICRA Conference 2018 Conference Paper

A Fluid-Filled Tubular Dielectric Elastomer Variable Stiffness Structure Inspired by the Hydrostatic Skeleton Principle *Research supported by the National Natural Science Foundation of China (No. 51675413)

Tao Wang
Yue Li
Yuanjie Li
Jinhua Zhang
Jun Hong 0002
Michael Yu Wang

This work presents a novel variable stiffness structure consisting of a fiber-constrained dielectric elastomer tube filled with insulating oil. The tensile stiffness of the structure can be adjusted by voltages and its initial value can be customized according to the initial pre-stretch of the material. The structure has a dimension of ∼30 mm diameter × 50 mm length. A mathematical analysis is established to predict the initial tensile stiffness of the structure. The changes of the tensile stiffness of the structure under voltages are verified experimentally. The results show a decrease of the tensile stiffness of the device by 25% at 4 kV and the decrement is also related to the elongation of the structure. With different pre-stretches and dimensions of the dielectric elastomer, one can obtain devices with different variation ranges of tensile stiffness.

ICRA Conference 2018 Conference Paper

Rearrangement with Nonprehensile Manipulation Using Deep Reinforcement Learning

Weihao Yuan 0001
Johannes A. Stork
Danica Kragic
Michael Yu Wang
Kaiyu Hang

Rearranging objects on a tabletop surface by means of nonprehensile manipulation is a task which requires skillful interaction with the physical world. Usually, this is achieved by precisely modeling physical properties of the objects, robot, and the environment for explicit planning. In contrast, as explicitly modeling the physical environment is not always feasible and involves various uncertainties, we learn a nonprehensile rearrangement strategy with deep reinforcement learning based on only visual feedback. For this, we model the task with rewards and train a deep Q-network. Our potential field-based heuristic exploration strategy reduces the amount of collisions which lead to suboptimal outcomes and we actively balance the training set to avoid bias towards poor examples. Our training process leads to quicker learning and better performance on the task as compared to uniform exploration and standard experience replay. We demonstrate empirical evidence from simulation that our method leads to a success rate of 85%, show that our system can cope with sudden changes of the environment, and compare our performance with human level performance.

ICRA Conference 2017 Conference Paper

A robotic manipulator design with novel soft actuators

Xiaojiao Chen
Jing Peng 0005
Jianshu Zhou
Yonghua Chen
Michael Yu Wang
Zheng Wang 0002

Soft robots are inherently compliant and adaptive, therefore they are promising candidates for interacting with humans. However robotic manipulators utilizing soft actuators are often constrained by a series of actuator performance limitations. In this work we design a novel linear soft robotic actuator with significantly improved performances over the existing products, achieving 300% deformation ratio, quasi-constant output force over a wide motion range, while maintaining passive compliance and adaptability. Moreover, the novel actuator is less prone to friction, and could be fabricated using inject molding and 3D printing, hence having high repeatability at very low cost. An analytical model was developed to characterize the actuator behavior and provide a guideline for actuator design according to performance specifications. A 6 DOF soft manipulator was designed and fabricated utilizing the novel soft actuator. The manipulator arm had a serial kinematic structure with a biomimetic wrist and was driven by 12 soft actuators mounted onto the arm links. With 1. 2m workspace radius and 1kg payload, the working air pressure could be as low as 1bar. Preliminary results have shown the validity of the novel soft actuator and manipulator designs, as well as the strong potential of soft robots in human-oriented applications.

IROS Conference 2017 Conference Paper

Design and development of a soft gripper with topology optimization

Hongying Zhang 0003
Michael Yu Wang
Feifei Chen 0002
Yiqiang Wang
A. Senthil Kumar
Jerry Y. H. Fuh

Soft robots, primarily made out of intrinsically soft materials, have flourished greatly in the past decade due to their advantages such as flexibility and adaptability over rigid-bodied robots. A rich repertoire of soft robots designed from intuitive or biomimetic approaches have been developed to provide new solutions for robots. However, these design approaches are limited by the designers' experience and inspiration, and a systematic design methodology for soft robots is still missing. We tackle this issue by mathematically recasting the design problem under the framework of topology optimization problem. To demonstrate the effectiveness of the proposed methodology, in this paper, we develop a pneumatically actuated soft gripper consisting of three fingers, each finger is able to undergo a free travel bending and deliver a grasping force. Hence, each gripper finger is designed as a continuum compliant mechanism to achieve its maximal bending deformation. The proposed soft gripper with complex shape is directly fabricated through 3D printing technology. Experimental results show that the deflected soft finger is able to achieve a 41° free travel bending and generate 0. 68N blocked force upon 0. 11MPa actuation pressure. This work represents an important step towards the goal of designing soft robots automatically.

ICRA Conference 2017 Conference Paper

Networked soft actuators with large deformations

Feifei Chen 0002
Jiawei Cao
Lei Zhang 0073
Hongying Zhang 0003
Michael Yu Wang
Jian Zhu 0005
Yunfeng Zhang

Soft actuators play an important role in producing motions in soft robots, and dielectric elastomers have shown great promise because of their considerable voltage-induced deformation. In particular, air-filled dielectric elastomer actuators have been well studied, where the air inside provides prestretches to improve the actuation range. This paper proposes a network of inflated dielectric elastomer actuators, interconnected via a chamber, with the advantages to be highly deformable and continuously controllable. Theoretical analyses show that the networked design is able to largely postpone the occurrence of material failures of the actuators, resulting in a large and continuous actuation range for their control. We further carried out experiments for validation, and the results were largely in line with the theoretical predictions. These findings essentially provide insight into developing networked soft actuators, for achieving large actuation capability.

ICRA Conference 2011 Conference Paper

Compliant fixture layout design using topology optimization method

Jie Ma
Michael Yu Wang
Xiangyang Zhu

The deformation of the workpiece-fixture system has essential influence on the locating accuracy of the workpiece. To minimize the overall deformation of the workpiece-fixture system is an important issue in fixture design. This paper focuses on the fixture layout design with compliant model. A topology optimization approach is presented in order to reduce the complexity introduced by the high computational cost of the finite element equation solving and the exhaustive search in the point set domain. With finite element analysis, algorithms are developed for the optimization problem of locator synthesis in the point set domain. Numerical examples are also presented to verify the effectiveness of the proposed approach.

IROS Conference 2010 Conference Paper

Expansion-based depth map estimation for multi-view stereo

Peng Song 0001
Xiaojun Wu 0004
Michael Yu Wang
Jianhuang Wu

This paper presents an algorithm for acquiring high-quality models from multiple calibrated photographs by computing and merging depth maps. The algorithm first computes depth maps from multi-view stereo using a proposed expansion-based approach that returns a 3D point cloud with noisy and redundant information. Then the estimated depth maps are merged into an accurate surface model by a cleaning, downsampling, surface normal estimation and Poisson surface reconstruction process. The proposed approach has been implemented and the experimental results with several real datasets demonstrate that the approach can produce accurate surface models efficiently.

ICRA Conference 2009 Conference Paper

Passive force analysis with elastic contacts for fixturing and grasping

Tong Liu 0003
Michael Yu Wang

Unlike active force closure, which is a property for the multi-finger robotic hand grasping, passive force closure are involved in the grasping systems with constraining devices that cannot freely control the contact forces, such as the whole-arm grasping and manufacturing fixture. In passive grasping, the contact forces rely on the physical compliance of the system which is usually described by complex contact mechanics models. The purpose of this paper is to study the properties of a type of contact model, the linear elastic contact model, so that it is possible to determine the passive force closure condition and to understand the essential characteristics of the passive grasping. The formula to solve the passive grasping forces is derived. Properties of the passive grasping is studied. The kinematic compatibility equation which describes the requirement of the coordination of contact forces is discovered, which is unique to the passive grasping. The algorithm to find the range of the preload to guarantee the passive force closure is deduced. The algorithm is demonstrated with two examples.

ICRA Conference 2007 Conference Paper

A Transparent Bilateral Controller for Teleoperation Considering the Transition of Motion

Heng Wang 0001
Bryan Kian Hsiang Low
Michael Yu Wang

A two-channel bilateral controller is proposed for teleoperation systems, which takes into account both the free space motion and the constrained motion. Specifically, the force-position (F-P) architecture is applied during the constrained motion, while the position-position (P-P) architecture is applied during the free space motion. Perfect transparency can be achieved in theory. In addition, the controller is robust to model uncertainties and disturbances, and it does not need to switch the control modes of the master and the slave controllers during the transition between the free space motion and the constrained motion. Experiments are conducted to demonstrate the effectiveness of the proposed bilateral controller.

ICRA Conference 2007 Conference Paper

Force Analysis of Whole Hand Grasp by Multifingered Robotic Hand

Jijie Xu
Michael Yu Wang
Hong Wang
Zexiang Li 0001

Under a whole hand grasp, it may not be possible to generate grasping forces in all directions. Thus, the traditional techniques developed based on fingertip contacts is inadequate. In this paper, we decompose the contact force space into four orthogonal subspaces, each with a clear physical interpretation. Based on linear matrix inequalities (LMI's) representations of grasping constraints, we address and formulate the active force closure and the active grasp feasibility problems as LMI feasibility problems. Combining the effects of both active and passive forces, we propose a new cost index for the whole hand grasping force optimization problem. We further simply the force optimization problem for a whole hand grasp, which is active force closure.

IROS Conference 2006 Conference Paper

Combined Impedance/Direct Control of Robot Manipulators

Heng Wang 0001
Kin Huat Low
Michael Yu Wang

In the basic impedance control structure, it is usually required to know the environment stiffness/impedance for precise force tracking. In addition, the performance may be degraded when the random external disturbances exist. By incorporating a PI-type compensator to the basic impedance control structure, this paper presents a combined impedance/direct control scheme for control of robot manipulators, which is characterized by high disturbance rejection, robustness to uncertainties, and simple structure for application. Moreover, it does not require to switch the control modes during the transition between the free space motion and the constrained motion. Therefore, the proposed controller combines the advantages of both the direct control and the impedance control. Computer simulations are performed to demonstrate the superiority of the proposed control scheme over the impedance control.

ICRA Conference 2005 Conference Paper

A Mapping Method for Telemanipulation of the Non-Anthropomorphic Robotic Hands with Initial Experimental Validation

Heng Wang 0001
Bryan Kian Hsiang Low
Michael Yu Wang
Feng Gong

A mapping algorithm is essential to teleoperate a robot hand. Joint-to-joint mapping, pose mapping and point-to-point mapping are three commonly used methods for telemanipulation. However, these methods might not produce satisfactory performance if the robot hand is non-anthropomorphic. This paper introduces a method for mapping based on the relative positions between fingertips. An algorithm particularly for a three-fingered non-anthropomorphic robot hand is presented. The principle of the method is to find suitable parameters in the hand frame, to transform them to the robot frame, and then to compute the robot fingertip positions according to the transformed parameters. The mapping results and the comparisons with the traditional methods validate the advantages of the proposed method.

ICRA Conference 2004 Conference Paper

Computation of Multi-rigid-body Contact Dynamics

Tong Liu 0003
Michael Yu Wang

A system of rigid bodies with multiple simultaneous contacts is considered in this paper. The problem is to predict the velocities of the bodies and the frictional forces acting on the simultaneous multi-contacts. This paper presents a numerical method based on an extension of an explicit time-stepping scheme and an application of the differential inclusion process introduced by J. J. Moreau. From the differential kinematic analysis of contacts, we derive a set of transfer equations in the velocity based time-stepping formulation. In applying the Gauss-Seidel iterative scheme, the transfer equations are combined with the Signorini conditions and Coulomb's friction law. The contact forces are properly resolved in each iteration, without resorting to any linearization of the friction cone. Numerical examples of the performance of the proposed method are compared with an acceleration-based scheme using linear complementarity techniques.

ICRA Conference 2003 Conference Paper

A computer-aided probing strategy for workpiece localization

Zhenhua Xiong 0003
Michael Yu Wang
Zexiang Li 0001

This paper presents an optimal planning problem for workpiece measurement. Two sequential optimization algorithms are introduced to find maximum determinant solutions. Then, based on a reliability analysis of workpiece localization and the sequential optimization algorithms, a computer-aided probing strategy is proposed. With this strategy, given the desired translation and orientation error bounds and desired confidence limit, we can experimentally find the least number of points needed to measure. Simulation results show the efficiency of the computer-aided probing strategy.

ICRA Conference 2003 Conference Paper

Force passivity in fixturing and grasping

Michael Yu Wang
Yun-Hui Liu 0001

While the classical notion of force closure is defined for actively controlled and coordinated robotic fingers, passive contacts play an equally important role in workpiece fixturing and often in robotic manipulation. This paper presents a description of passive forces arising at the normal and frictional contacts by passive physical means. The passive contacts generate reactive forces only as a response to an external force and/or any active force. Within the framework of rigid body contact, a contact system with passive forces is generally undeterminate. We present a general approach based on an application of the minimum norm principle. The model reveals some intricate properties of the passive contact forces, including internal forces at the passive and/or active contacts. Some practical implications of the passive nature in fixture design are discussed.

IROS Conference 2002 Conference Paper

A full contact model for fixture kinematic analysis

Michael Yu Wang
Tong Liu 0003

The conventional point-kinematic model of fixtures only treats point geometry of the contacts between locators and the workpiece. However, this model, which ignores the underlying surface properties of the locators-plus-workpiece system, is inherently incapable of capturing the effects of the geometric properties important to accurate positioning of the workpiece. In this paper, we present a fixture kinematic analysis based on the full kinematics of locator-workpiece contact. This model incorporates a "virtual" kinematic chain with meshing parameters of contact kinematics in a velocity formulation. Conditions of a deterministic fixture are derived. It is shown that the workpiece position and orientation are completely characterized by the kinematic properties of the locator contacts with the workpiece, including not only the arbitrary locator location errors but also the surface properties at non-prismatic locator-workpiece contacts. This is illustrated with numerical examples. The fixture kinematic analysis developed here has a strong implication for designing fixtures with high locating precision requirements.

ICRA Conference 2002 Conference Paper

Characterization of Positioning Accuracy of Deterministic Localization of Fixtures

Michael Yu Wang

In this article an analysis is presented to the problem of characterizing the accuracy of deterministic localization of fixtures. In a statistical framework, the positioning accuracy of the workpiece localized by the locators of a fixture is described by a symmetric, positive-definite accurateness matrix (or variance matrix). The accurateness (variance) matrix is identified to have similar structural properties to the stiffness (compliance) matrix of an unloaded, stable robot grasp. This connection leads us to describe a set of frame-invariant characteristic parameters with geometric interpretation. The principal translational accuratenesses and rotational variances are defined for constructions of frame-invariant quality measures for a meaningful comparison of different locating schemes. An example is presented to illustrate the concept and usefulness of the characterizing properties in optimizing a fixture layout.

ICRA Conference 2002 Conference Paper

Fixture Layout Design for Curved Workpieces

Dan Ding
Guoliang Xiang
Yun-Hui Liu 0001
Michael Yu Wang

In this paper, we propose an approach to design a proper fixture layout for a 3D curved workpiece. The problem is tackled in a point set domain by discretizing the exterior surface of the workpiece into a dense collection of candidate fixturing points and then searching for a small proper set of fixturing points that satisfies the total restraint of the workpiece and reduces the workpiece positioning error. The algorithm first randomly selects an initial set of seven fixturing points and then iteratively improves it by exchanging with the other candidate points through a best-first strategy and a randomized motion. Finally, the algorithm has been implemented and its efficiency has been ascertained by two examples.

IROS Conference 2001 Conference Paper

Automatic selection of fixturing surfaces and fixturing points for polyhedral workpieces

Dan Ding
Yun-Hui Liu 0001
Michael Yu Wang

Fixtures play an important role in many manufacturing operations such as inspection, machining and part fabrication. In the development of a fixture, it is desired that the feasible fixturing surfaces and optimal fixturing locations on the workpiece be selected automatically. An algorithm is presented to determine optimal fixturing locations which totally restrain the workpart in the fixture without being disturbed by any external force. First, based on observation that form-closure fixturing points exist on a set of surfaces if and only if the convex hull of the vertex contact wrenches resulting from the vertices of the surfaces contains the origin of R/sup 6/, an efficient approach is developed for finding an eligible set of fixturing surfaces. Second, we formulate the problem of determining optimal fixturing points on the eligible set of fixturing surfaces as a quadratic programming (QP) problem with the workpiece positioning accuracy as the performance index and the robust form-closure requirement as the linear constraints. Finally, the implementation for two numerical examples demonstrates the usefulness and efficiency of the proposed algorithm.

ICRA Conference 2001 Conference Paper

Optimal Fixture Layout Design in a Discrete Domain for 3D Workpieces

Michael Yu Wang
Diana M. Pelinescu

This paper addresses two major issues in fixture layout design: 1) to determine the feasible fixture configurations that satisfy fundamental requirements suck as kinematic localization and total fixturing (form-closure); and 2) to evaluate the acceptable fixture designs on several quality criteria and select the optimal fixture appropriate with practical demands. The performance objectives considered include the workpiece localization accuracy, and the norm and distribution of the locator contact forces. An efficient automated tool based on an interchange algorithm is developed for designing optimal fixture layout for arbitrary 3D parts. A thorough analysis is performed on the fixture characteristics during the single and multicriteria optimization process for different frequent cases, and on the inter-relationship between locators and clamps, leading to conclusions and strategies for performing fixture synthesis.

ICRA Conference 2000 Conference Paper

Precision Localization and Robust Force Closure in Fixture Layout Design for 3D Workpieces

Michael Yu Wang
Diana M. Pelinescu

Addresses two issues in fixture layout design for 3D workpieces: (1) precision workpiece localization and (2) robust force-closure. An analysis is given to quantify these two fundamental requirements. Based on a concept of optimum experiment design, the optimal fixture design problems are treated to select optimal locators and clamps. An interchange algorithm is described, in which the fixture locators are generated sequentially first and are further improved. The algorithms use multiple criteria to balance the demands for precision localization and robust force closure. Examples are presented to illustrate the issues and to show the effectiveness of the proposed approach.

ICRA Conference 1999 Conference Paper

Automated Fixture Layout Design for 3D Workpieces

Michael Yu Wang

This paper presents a new approach to the problem of fixture layout design for 3D workpieces. The approach is based on a concept of optimum experiment design, and the problem is treated as an optimal aggregation to select optimal locators from an initial collection of a large number of fixel locations on the surfaces of the given workpiece and to achieve form-closure for the part. An interchange algorithm is described, in which the fixture locators are generated sequentially first and are further improved. The algorithm uses the D-optimality criterion to minimize the workpiece positioning error. An example of turbine airfoil is presented to illustrate the effectiveness of the proposed approach.

ICRA Conference 1996 Conference Paper

Optimal layout design of automated systems using topology connectivity method

Chris J. J. Lu
K. H. Tsai
Jackson C. S. Yang
Michael Yu Wang

Factory and facility automation has been widely implemented since the revolution of computers. A variety of automatic material processing machines and material handling equipment have been designed and manufactured for various applications. The facility layout optimization is one of the major tasks in designing automated systems. This paper proposes a generic methodology that provides a systematic way to design an optimal layout for all types of automated facilities. The quantitative design criteria of automatic material processing machines and material handling equipment are addressed first. An optimal connectivity among machines is then solved through topology approach and heuristic algorithm. Thus, an optimized facility layout can be derived and completed by combining the optimal topology connectivity, physical constraints, and designer's preference.

ICRA Conference 1989 Conference Paper

Dynamics and planning of collisions in robotic manipulation

Michael Yu Wang

The author treats the problem of collision between a robot end-effector and the manipulated object in robot catching. By applying rigid-body impact mechanics, intermittent dynamics involving a sequence of collisions is modeled by a difference-algebraic system. Through a stability analysis, the author presents open-loop strategies to perform a task using a paddlelike end-effector to catch a circular object in two-dimensional space. Computer simulation results have shown that the strategies are reliable and effective. The generalization of the method to more general robotic manipulation in dynamical environments is also discussed. >