Author name cluster

Chee-Meng Chew

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

21 papers

1 author row

IROS Conference 2022 Conference Paper

Real-time Digital Double Framework to Predict Collapsible Terrains for Legged Robots

Garen Haddeler
Hari P. Palanivelu
Yung Chuen Ng
Fabien Colonnier
Albertus H. Adiwahono
Zhibin Li 0001
Chee-Meng Chew
Meng Yee Michael Chuah

Inspired by the digital twinning systems, a novel real-time digital double framework is developed to enhance robot perception of the terrain conditions. Based on the very same physical model and motion control, this work exploits the use of such simulated digital double synchronized with a real robot to capture and extract discrepancy information between the two systems, which provides high dimensional cues in multiple physical quantities to represent differences between the modelled and the real world. Soft, non-rigid terrains cause common failures in legged locomotion, whereby visual perception solely is insufficient in estimating such physical properties of terrains. We used digital double to develop the estimation of the collapsibility, which addressed this issue through physical interactions during dynamic walking. The discrepancy in sensory measurements between the real robot and its digital double are used as input of a learning-based algorithm for terrain collapsibility analysis. Although trained only in simulation, the learned model can perform collapsibility estimation successfully in both simulation and real world. Our evaluation of results showed the generalization to different scenarios and the advantages of the digital double to reliably detect nuances in ground conditions.

IROS Conference 2020 Conference Paper

Explore Bravely: Wheeled-Legged Robots Traverse in Unknown Rough Environment

Garen Haddeler
Jianle Chan
Yangwei You
Saurab Verma
Albertus H. Adiwahono
Chee-Meng Chew

This paper addressed a challenging problem of wheeled-legged robots with high degrees of freedom exploring in unknown rough environments. The proposed method works as a pipeline to achieve prioritized exploration comprising three primary modules: traversability analysis, frontier-based exploration and hybrid locomotion planning. Traversability analysis provides robots an evaluation about surrounding terrain according to various criteria ( roughness, slope etc.) and other semantic information (small step, stair, bridge etc.), while novel gravity point frontier-based exploration algorithm can effectively decide which direction to go even in unknown environments based on robots' current pose and desired one. Given all these information, hybrid locomotion planner will generate a path with motion mode (driving or walking) encoded by optimizing among different objectives and constraints. Lastly, our approach was well verified in both simulation and experiment on a wheeled quadrupedal robot Pholus.

ICRA Conference 2020 Conference Paper

PointAtrousGraph: Deep Hierarchical Encoder-Decoder with Point Atrous Convolution for Unorganized 3D Points

Liang Pan
Chee-Meng Chew
Gim Hee Lee

Motivated by the success of encoding multi-scale contextual information for image analysis, we propose our PointAtrousGraph (PAG) - a deep permutation-invariant hierarchical encoder-decoder for efficiently exploiting multi-scale edge features in point clouds. Our PAG is constructed by several novel modules, such as Point Atrous Convolution (PAC), Edgepreserved Pooling (EP) and Edge-preserved Unpooling (EU). Similar with atrous convolution, our PAC can effectively enlarge receptive fields of filters and thus densely learn multi-scale point features. Following the idea of non-overlapping maxpooling operations, we propose our EP to preserve critical edge features during subsampling. Correspondingly, our EU modules gradually recover spatial information for edge features. In addition, we introduce chained skip subsampling/upsampling modules that directly propagate edge features to the final stage. Particularly, our proposed auxiliary loss functions can further improve our performance. Experimental results show that our PAG outperform previous state-of-the-art methods on various 3D semantic perception applications.

IROS Conference 2019 Conference Paper

EPN: Edge-Aware PointNet for Object Recognition from Multi-View 2. 5D Point Clouds

Syeda Mariam Ahmed
Pan Liang
Chee-Meng Chew

Performance of current 3D point based detectors is limited by the number of points they can process, consequently limiting their accuracy. In this paper we propose a novel architecture coined as Edge-Aware PointNet, that incorporates geometric shape priors as binary maps, integrated in parallel with the PointNet++ framework, through convolutional neural networks (CNNs). The proposed architecture takes individual object instances as input and learns the task of object recognition for 3D shapes. To train the network, we present a dataset of 31k 2. 5D synthetic point clouds rendered from ModelNet40. Through 2. 5D representation, the network learns object recognition despite occlusion that enables improved performance on objects from real world, while 2D binary maps enable feature learning that is independent of number of points in the point cloud. Comprehensive experimentation shows that the proposed network is able to improve performance by 2. 5% on ModelNet40 and 2. 6% on ModelNet10 datasets, as compared to the baseline PointNet++. We also show improved performance as compared to state-of-the-art methods, on a real world RGBD dataset where our network improves results by 8%. Our code and dataset is publicly available at github.com/Merium88/Edge-Aware-PointNet.

IROS Conference 2018 Conference Paper

Edge and Corner Detection for Unorganized 3D Point Clouds with Application to Robotic Welding

Syeda Mariam Ahmed
Yan Zhi Tan
Chee-Meng Chew
Abdullah Al Mamun 0002
Fook Seng Wong

In this paper, we propose novel edge and corner detection algorithms for unorganized point clouds. Our edge detection method evaluates symmetry in a local neighborhood and uses an adaptive density based threshold to differentiate 3D edge points. We extend this algorithm to propose a novel corner detector that clusters curvature vectors and uses their geometrical statistics to classify a point as corner. We perform rigorous evaluation of the algorithms on RGB-D semantic segmentation and 3D washer models from the ShapeNet dataset and report higher precision and recall scores. Finally, we also demonstrate how our edge and corner detectors can be used as a novel approach towards automatic weld seam detection for robotic welding. We propose to generate weld seams directly from a point cloud as opposed to using 3D models for offline planning of welding paths. For this application, we show a comparison between Harris 3D and our proposed approach on a panel workpiece.

IROS Conference 2017 Conference Paper

A frog-inspired swimming robot based on dielectric elastomer actuators

Yucheng Tang
Lei Qin
Xiaoning Li
Chee-Meng Chew
Jian Zhu 0005

Frogs are capable of multiple locomotion modes including jumping and swimming, which enables them to adapt to various environmental conditions. This paper demonstrates a frog-inspired robot, which can mimic the swimming motion of a natural frog. The robot is developed based on dielectric elastomer actuators, which exhibits muscle-like behavior such as large voltage-induced deformation, high energy density, fast response and low weight. Inspired by the webbed feet of a frog, the foot actuator of the swimming robot is able to increase its projected area by 66% when subject to high voltage. Actuation of the foot actuators can significantly improve the averaged peak thrust by 34. 5%. The total mass of the two dielectric elastomer actuators is 14g which only accounts for 13% of its total mass of 108g. The measured average swimming speed for a square wave voltage of 5kV and 0. 25Hz is 19mm/s for the swimming robot. Future work of the project includes optimal design and control of this soft robot.

IROS Conference 2017 Conference Paper

Study of sweep angle effect on thrust generation of oscillatory pectoral fins

Chee-Meng Chew
Soheil Arastehfar
Gunawan
Khoon Seng Yeo

Manta ray's pectoral fins have been a great source of inspiration for propulsive mechanism of autonomous underwater vehicles, due to their propulsive capability. The geometry (shape) and flexibility factors of these fins have been hypothesized to be determinants of the propulsive capability of the fins in terms of thrust generation. In particular, the sweep angle factor has been omitted from previous studies, where it has been commonly set to about 30 degrees. This paper investigates the effects of sweep angle on thrust generation of oscillatory pectoral fins. Forty different fins were designed and fabricated to be experimented in a water channel, which involved measurement of thrust generated by the fins. The experiment was conducted under free stream (0. 5 m/s) and still water conditions. Five different sweep angles (0, 10, 20, 30, 40 degrees) were incorporated into eight base designs of different flexibility characteristics to make up the 40 fins. To consider only sweep angle, other geometrical factors were not varied. Within the range of the sweep angle considered, the experimental results showed that sweep angle has no significant influence on the fins' thrust generation, under both free stream and still water conditions. Overall, it can be concluded that sweep angle may not be a determinant of oscillatory pectoral fins' thrust generation.

IROS Conference 2016 Conference Paper

Object detection and motion planning for automated welding of tubular joints

Syeda Mariam Ahmed
Yan Zhi Tan
Gim Hee Lee
Chee-Meng Chew
Chee Khiang Pang

Automatic welding of tubular TKY joints is an important and challenging task for the marine and offshore industry. In this paper, a framework for tubular joint detection and motion planning is proposed. The pose of the real tubular joint is detected using RGB-D sensors, which is used to obtain a real-to-virtual mapping for positioning the workpiece in a virtual environment. For motion planning, a Bi-directional Transition-based Rapidly exploring Random Tree (BiTRRT) algorithm is used to generate trajectories for reaching the desired goals. The complete framework is verified with experiments, and the results show that the robot welding torch is able to transit without collision to desired goals which are close to the tubular joint.

IROS Conference 2015 Conference Paper

Application of deep neural network in estimation of the weld bead parameters

Soheil Keshmiri
Xin Zheng
Wen Feng Lu
Chee Khiang Pang
Chee-Meng Chew

We present a deep learning approach to estimation of the bead parameters in welding tasks. Our model is based on a four-hidden-layer neural network architecture. More specifically, the first three hidden layers of this architecture utilize Sigmoid function to produce their respective intermediate outputs. On the other hand, the last hidden layer uses a linear transformation to generate the final output of this architecture. This transforms our deep network architecture from a classifier to a non-linear regression model. We compare the performance of our deep network with a selected number of results in the literature to show a considerable improvement in reducing the errors in estimation of these values. Furthermore, we show its scalability on estimating the weld bead parameters with same level of accuracy on combination of datasets that pertain to different welding techniques. This is a nontrivial result that is counter-intuitive to the general belief in this field of research.

IROS Conference 2015 Conference Paper

Identification and reconstruction of complex weld geometry based on modified entropy

Soheil Keshmiri
Yan Zhi Tan
Xin Zheng
Syeda Mariam Ahmed
Yue Wu
Wen Feng Lu
Chee-Meng Chew
Chee Khiang Pang

In this paper, a modified entropy-based algorithm is proposed for identification and reconstruction of a complex weld geometry. The edge of the weld geometry is identified based on minimizing a modified entropy-type cost function, and the weld geometry is reconstructed based on the detected edge. In addition, the volume of the weld geometry is computed using the point cloud samples of the identified weld geometry, and the effects of Gaussian noise are also considered. Our simulation results using the proposed reconstruction algorithm demonstrate efficient identification and reconstruction of a complex weld geometry in the presence of Gaussian noise.

ICRA Conference 2014 Conference Paper

Functional task based assistance during walking for a Lower Extremity Assistive Device

Bingquan Shen
Jinfu Li 0001
Chee-Meng Chew

In this paper, we propose a functional task based assistance controller to aid user in the walking task with our Lower Extremity Assistive Device (LEAD). Firstly, a gait period detector, which utilizes a Gaussian Mixture Model (GMM), is developed to estimate the user's current gait period among the six major periods. Then, an impedance based controller is used to apply assistive torques to the hip and knee joints of the user based on the functional task intended at the current gait period. To validate the above control scheme, preliminary experiments have been performed with one healthy subject walking on a treadmill. The results show that the gait period detector can effectively detect each gait period for the whole cycle. Based on measurements of the heart rate, the proposed assistance method has shown that it can effectively assist a human user in walking at speed of 1 km/h.

IROS Conference 2013 Conference Paper

Standing posture modeling and control for a humanoid robot

Syeda Mariam Ahmed
Chee-Meng Chew
Bo Tian

This paper presents a novel approach employing nonlinear control for stabilization of standing posture for a humanoid robot using only hip joint. The robot is modeled as an acrobot where model parameters are estimated through adaptive algorithm. A `non-collocated partial feedback' controller is applied. This is integrated with a linear feedback control, through LQR. Improved robustness to external push is demonstrated through evaluation in Webots simulator and on a physical humanoid robot, NUSBIP-III ASLAN. Performance comparison with other controllers verifies the effectiveness of the proposed control system.

IROS Conference 2010 Conference Paper

A walking pattern generator for biped robots on uneven terrains

Yu Zheng 0001
Ming Lin 0003
Dinesh Manocha
Albertus H. Adiwahono
Chee-Meng Chew

We present a new method to generate biped walking patterns for biped robots on uneven terrains. Our formulation uses a universal stability criterion that checks whether the resultant of the gravity wrench and the inertia wrench of a robot lies in the convex cone of the wrenches resulting from contacts between the robot and the environment. We present an algorithm to compute the feasible acceleration of the robot's CoM (center of mass) and use that algorithm to generate biped walking patterns. Our approach is more general and applicable to uneven terrains as compared with prior methods based on the ZMP (zero-moment point) criterion. We highlight its applications on some benchmarks.

IROS Conference 2010 Conference Paper

Proposal of Augmented Linear Inverted Pendulum model for bipedal gait planning

Van-Huan Dau
Chee-Meng Chew
Aun Neow Poo

In this paper, we propose a new model called Augmented Linear Inverted Pendulum (ALIP) in which an augmented function F is added to the dynamic equation of the linear inverted pendulum. The purpose of adding the function F is to modify/adjust the inverted pendulum dynamics in such a way that disturbance caused by un-modeled dynamics (legs, arms, etc.) can be compensated or minimized. By changing the key parameters of the augmented function we can easily modify the inverted pendulum dynamics. The desired walking motion with maximized stability margin is achieved by optimizing the key parameters using genetic algorithm. The disturbance created by the un-modeled dynamics is minimized because full robot dynamics is considered in the optimization process. Simulations results show that the walking gait obtained using the proposed method is more stable than that obtained using the Linear Inverted Pendulum Mode (LIPM).

ICRA Conference 2009 Conference Paper

A numerical solution to the ray-shooting problem and its applications in robotic grasping

Yu Zheng 0001
Chee-Meng Chew

Based on the distance algorithm by Gilbert et al. , this paper presents a numerical algorithm for computing the intersection of the boundary of a compact convex set with a ray emanating from an interior point of the set, which is known as the ray-shooting problem. Affinely independent points on the boundary of the convex set are also determined such that the intersection point can be written as their convex combination. Because of its high efficiency and other good qualities, this algorithm provides superior solutions to three fundamental problems in robotic grasping, i. e. , force-closure test, contact force optimization, and grasp quality evaluation, which can be formulated as the ray-shooting problem.

ICRA Conference 2008 Conference Paper

Coordination between oscillators: An important feature for robust bipedal walking

Weiwei Huang 0005
Chee-Meng Chew
Geok-Soon Hong

Biological inspired control approaches based on central pattern generator (CPG) have been used to generate human-like rhythmic locomotion for bipedal robots. CPG consists of several oscillators with coupled mutual inhibition. In the application of CPG to bipedal walking, one of the important problem is how to coordinate oscillators so as to achieve stable walking, since without proper coordination the rhythmic trajectory generated by CPG may fail to control the walking. To solve this problem, this paper presents a method of coordination between two oscillators using phase information. In the method, approximated phase values of the oscillators are derived and used as the feedback to coordinate two oscillators. Furthermore, coordination between multiple oscillators with different frequencies and phases has also been explored. This method is verified with a 2D robust walking controlled by four oscillators. Several walking scenarios are tested: adding external force, change walking frequency and step length during walking. Robust walking is achieved in our simulation.

IROS Conference 2006 Conference Paper

Adjustable Bipedal Gait Generation using Genetic Algorithm Optimized Fourier Series Formulation

Lin Yang
Chee-Meng Chew
Aun Neow Poo
Teresa Zielinska

This paper presents a method for optimally generating stable bipedal walking gaits, based on a truncated Fourier series formulation with coefficients tuned by genetic algorithm. It also provides a way to adjust the stride-frequency, step-length or walking pattern in real-time. The proposed approach to gait synthesis is not limited by the robot kinematic structure and can be used to satisfy various motion assumptions. It is also easy to generate optimal gaits on terrains of different slopes or on stairs under different motion requirements. Dynamic simulation results show the validity and robustness of the approach. The gaits generated resulted in human-like motions optimized for stability, even walking speed and lower leg-strike velocity of the swing foot

ICRA Conference 2003 Conference Paper

Frontal Plane Algorithms for Dynamic Bipedal Walking

Chee-Meng Chew
Gill A. Pratt

This paper presents two frontal plane algorithms for 3D dynamic bipedal walking. One of which is based on the notion of symmetry and the other uses reinforcement learning algorithm to learn the lateral foot placement. The algorithms are combined with a sagittal plane algorithm and successfully applied to a simulated 3D bipedal robot to achieve level ground walking. The simulation results showed that the choice of the local control law for the stance-ankle roll joint could significantly affect the performance of the frontal plane algorithms.

ICRA Conference 2000 Conference Paper

A General Control Architecture for Dynamic Bipedal Walking

Chee-Meng Chew
Gill A. Pratt

We propose a general but simple bipedal walking control architecture that incorporates intuitive control and learning algorithms. The learning algorithm is mainly used to generate the key parameters for the swing leg. The intuitive control is used to maintain the height and body posture. Based on the proposed architecture, a control algorithm is constructed and applied to a planar biped and a 3D biped. By applying an appropriate local speed control mechanism, we demonstrate that the bipeds can successfully achieve walking of 100 seconds within a reasonable number of trials. No dynamic models or nominal joint trajectory data are required for the implementations.

IROS Conference 1999 Conference Paper

A minimum model adaptive control approach for a planar biped

Chee-Meng Chew
Gill A. Pratt

Virtual model control (VMC) has previously been successfully applied to steady dynamic walking of a planar biped. This control methodology requires very low computation because it does not calculate the inverse dynamics of the biped. An adaptive control approach based on radial basis function neural networks (RBFNNs) has also been previously proposed to enhance VMC. However, such implementation is computationally intensive. We propose a simpler adaptive VMC that allows the biped to adapt to mass variations without using RBFNNs. We implement the resulting system and demonstrate the robustness of the implementation by simulating the biped walking over rolling terrain.

ICRA Conference 1999 Conference Paper

Blind Walking of a Planar Bipedal Robot on Sloped Terrain

Chee-Meng Chew
Jerry E. Pratt
Gill A. Pratt

Simple intuitive control strategies can be used to compel bipedal robots to walk over sloped terrain. We describe an algorithm for walking dynamically and steadily over sloped terrain with unknown slope gradients and transition locations. The algorithm is developed based on geometric considerations. The overall algorithm is very simple and does not require the biped to have an extensive sensory system for walking over moderate slopes. The ground is detected blindly using only foot contact switches. Using a few simple strategies, we have compelled a simulated 7-link planar biped to walk up and down slopes and over rolling terrain.