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Chad C. Kessens

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.

11 papers

1 author row

ICRA Conference 2024 Conference Paper

Amortized Inference for Efficient Grasp Model Adaptation

Michael Noseworthy
Seiji Shaw
Chad C. Kessens
Nicholas Roy

In robotic applications such as bin-picking or block-stacking, learned predictive models have been developed for manipulation of objects with varying but known dynamic properties (e. g. , mass distributions and friction coefficients). When a robot encounters a new object, these properties are often difficult to observe and must be inferred through interaction, which can be expensive in both inference time and number of interactions. We propose an encoder/decoder action-feasibility model to efficiently adapt to new objects by estimating their unobserved properties through interaction. The encoder predicts a distribution over the unobserved parameters while the decoder predicts action feasibility, which can be used in an uncertainty-aware planner. An explicit representation of uncertainty in the encoder enables information-gathering heuristics to minimize adaptation interactions. The amortized distributions are efficient to compute and perform comparably to particle-based distributions in a grasping domain. Finally, we deploy our method on a Panda robot to grasp heavy objects.

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ICRA Conference 2024 Conference Paper

Johnsen-Rahbek Capstan Clutch: A High Torque Electrostatic Clutch

Timothy E. Amish
Jeffrey T. Auletta
Chad C. Kessens
Joshua R. Smith 0001
Jeffrey I. Lipton

In many robotic systems, the holding state consumes power, limits operating time, and increases operating costs. Electrostatic clutches have the potential to improve robotic performance by generating holding torques with low power consumption. A key limitation of electrostatic clutches has been their low specific shear stresses which restrict generated holding torque, limiting many applications. Here we show how combining the Johnsen-Rahbek (JR) effect with the exponential tension scaling capstan effect can produce clutches with the highest specific shear stress in the literature. Our system generated 31. 3 N/cm 2 sheer stress and a total holding torque of 7. 1 N•m while consuming only 2. 5 mW/cm 2 at 500 V. We demonstrate a theoretical model of an electrostatic adhesive capstan clutch and demonstrate how large angle (θ > 2π) designs increase efficiency over planar or small angle (θ < π) clutch designs. We also report the first unfilled polymeric material, polybenzimidazole (PBI), to exhibit the JR-effect.

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ICRA Conference 2024 Conference Paper

Toward Self-Righting and Recovery in the Wild: Challenges and Benchmarks

Rosario Scalise
Ege Caglar
Byron Boots
Chad C. Kessens

Self-recovery is a critical capability for robust, agile robots operating in the real world. Given truly challenging terrain, it is nearly inevitable that, at some point, the robot will fail and subsequently need to recover if it is to continue its task. One critical subset of recovery is standing back up after falling down (aka "self-righting"), an essential early milestone for babies learning to walk, and an existential capability for animals. While some robots can be designed with multiple orientations for mobility, most seeking to affect the world would significantly benefit from planners/policies that facilitate self-righting whenever possible. In this work, we present a series of challenges that outline why recovery in the wild is difficult. We then present a set of benchmark policies trained in simulation using deep reinforcement learning (RL) and the Student-Teacher approach. Finally, we evaluate the performance of these policies on a set of benchmark contexts in simulation, and provide baseline validation on a physical robot.

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ICRA Conference 2019 Conference Paper

Toward Lateral Aerial Grasping & Manipulation Using Scalable Suction

Chad C. Kessens
Matthew Horowitz
Chao Liu 0021
James M. Dotterweich
Mark Yim
Harris L. Edge

This paper is an initial step toward the realization of an aerial robot that can perform lateral physical work, such as drilling a hole or fastening a screw in a wall. Aerial robots are capable of high maneuverability and can provide access to locations that would be difficult or impossible for ground-based robots to reach. However, to fully utilize this mobility, systems would ideally be able to perform functional work in those locations, requiring the ability to exert lateral forces. To substantially improve a hovering vehicle's ability to stably deliver large lateral forces, we propose the use of a versatile suction-based gripper that can establish pulling contact on featureless surfaces. Such contact enables access to environmental forces that can be used to further stabilize the vehicle and also increase the lateral force delivered to the surface through a possible secondary mechanism. This paper introduces the concept, describes the design of a new self-sealing suction cup based on a previous design, details the design of a gripper using those cups, and describes the arm and flight vehicle. It then evaluates the cup and gripper performance in several ways, culminating in physical grasping demonstrations using the arm and gripper, including one in the presence of simulated flight noise based on data from preliminary indoor flight experiments.

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IROS Conference 2016 Conference Paper

Cockroach-inspired winged robot reveals principles of ground-based dynamic self-righting

Chen Li 0017
Chad C. Kessens
Austin Young
Ronald S. Fearing
Robert J. Full

Animals and robots alike face challenges of flipping-over as they move in complex terrain. Small insects like cockroaches can rapidly right themselves when upside down, yet small fast-running legged robots are much less capable of ground-based self-righting. Inspired by the discoid cockroach that opens its wings to push against the ground to self-right, we designed actuated wings for robot self-righting based on recently-developed rounded shells for obstacle traversal [1]. We measured the self-righting performance of a robot using these actuated wings, and systematically studied the effects and trade-offs of wing opening magnitude, speed, symmetry, and wing geometry. Our study provided a proof-of-concept that robots can take advantage of an existing body structure (rounded shell) in novel ways (as actuated wings) to serve new locomotor functions, analogous to biological exaptations [2]. Our results demonstrated that the robot self-rights dynamically, with active wing pushing followed by passive falling, and benefits from increasing kinetic energy by pushing faster and longer. Our experiments also showed that opening both wings asymmetrically increases righting probability at low wing opening magnitudes.

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ICRA Conference 2016 Conference Paper

Versatile aerial grasping using self-sealing suction

Chad C. Kessens
Justin Thomas
Jaydev P. Desai
Vijay Kumar 0001

This paper addresses the challenge of versatile aerial grasping utilizing suction while considering the limitations of an on-board vacuum pump. It builds upon our patented self-sealing suction cup technology, which allows the exertion of local pulling contact forces for grasping a wide range of objects. The novel self-sealing nature of the cups enables the gripper to be versatile, employing just one, several, or all of the cups for the grasp in a passively actuated manner. We begin by describing the design of the system and its components. Because aerial applications are typically sensitive to weight constraints, we used a micro-pump vacuum generator, which introduced new challenges for our system. To investigate and overcome those challenges, we tested the relationship between the cup's design and its leakage, activation force, and maximum holding force. In addition, we tested the performance of the individual gripper components, the aerial vehicle's ability to transfer force to the cups, the system's ability to grip inclined surfaces, and finally the vehicle's ability to grasp a multitude of objects using various numbers of cups. This included the grasping of one object, followed by the grasping of a second object while still holding the first object.

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IROS Conference 2014 Conference Paper

A metric for self-rightability and understanding its relationship to simple morphologies

Chad C. Kessens
Craig T. Lennon
Jason Collins

To robustly operate in dynamic, unknown environments, robots should be able to autonomously recover from simple errors such as tip-over. Most efforts to date have introduced specific techniques applied as point solutions on simple terrain. For a more general solution, we previously introduced a framework for analyzing and generating solutions to the self-righting problem for a generic robot. In this paper, we turn our attention toward understanding how a robot's morphology affects its ability to self-right. We begin by briefly reviewing our framework, which is used to generate the results within the paper. We then introduce a self-rightability metric that can be used to evaluate a given robot design's potential for self-righting. It can also be used to compare disparate designs. Next, we show how the metric can be used to perform a parametric study covering multiple design variables for a simple robot class. In this way, we hope to enable designers to begin to understand how design parameters such as joint limits, limb length, limb to body mass ratio, limb mass location, and body aspect ratio will affect the robot's ability to self-right on a variety of ground angles. Finally, we show a case study of limb mass and validate results using a modular, 3 degree of freedom physical robot. Ultimately, we hope to enable the production of robots that are more capable of autonomously self-righting.

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ICRA Conference 2012 Conference Paper

A framework for autonomous self-righting of a generic robot on sloped planar surfaces

Chad C. Kessens
Daniel Carlton Smith
Philip R. Osteen

Increasingly, robots are being applied to challenges in dynamic, unstructured environments including urban search and rescue (USAR), planetary exploration, and military missions. During the execution of these missions, the robot may unintentionally tip over, rendering it unable to move normally. The ability to self-right and recover in such situations is crucial to mission completion and safe robot recovery. However, to date, nearly all self-righting solutions have been point solutions, each designed for a specific platform. As a first step toward a generic solution, this paper presents a framework for analyzing the self-righting capabilities of any generic robot on sloped planar surfaces. Based on the planar assumption, interactions with the ground can be defined entirely in terms of the robot's convex hull. Motion of arms, legs, or other appendages may change the convex hull shape and/or center of mass position, affecting the robot's orientation. Our framework for solving this problem can be summarized as follows: first, for each stable conformation, we analyze the position of the center of mass relative to the vertical projection of the convex hull face in contact with the ground. From this, we develop a conformation space map, defining stable state sets as nodes and the conformations where discontinuous state changes occur as transitions. Finally, we convert this map into a directed graph, and assign costs to the transitions according to changes in potential energy between states. Based upon the ability to traverse this directed graph to the goal state, one can analyze a robot's ability to self-right. To illustrate each step in our framework, we use a simple two-dimensional robot with a one degree of freedom arm, and then show a case study of iRobot's 510 Packbot®. Ultimately, we project that this framework will be useful both for designing robots with the ability to self-right and for planning joint movements to achieve efficient, autonomous self-righting behaviors.

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ICRA Conference 2012 Conference Paper

Online egomotion estimation of RGB-D sensors using spherical harmonics

Philip R. Osteen
Jason L. Owens
Chad C. Kessens

We present a technique to estimate the egomotion of an RGB-D sensor based on rotations of functions defined on the unit sphere. In contrast to traditional approaches, our technique is not based on image features and does not require correspondences to be generated between frames of data. Instead, consecutive functions are correlated using spherical harmonic analysis. An Extended Gaussian Image (EGI), created from the local normal estimates of a point cloud, defines each function. Correlations are efficiently computed using Fourier transformations, resulting in a 3 Degree of Freedom (3-DoF) rotation estimate. An Iterative Closest Point (ICP) process then refines the initial rotation estimate and adds a translational component, yielding a full 6-DoF egomotion estimate. The focus of this work is to investigate the merits of using spherical harmonic analysis for egomotion estimation by comparison with alternative 6-DoF methods. We compare the performance of the proposed technique with that of stand-alone ICP and image feature based methods. As with other egomotion techniques, estimation errors accumulate and degrade results, necessitating correction mechanisms for robust localization. For this report, however, we use the raw estimates; no filtering or smoothing processes are applied. In-house and external benchmark data sets are analyzed for both runtime and accuracy. Results show that the algorithm is competitive in terms of both accuracy and runtime, and future work will aim to combine the various techniques into a more robust egomotion estimation framework.

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ICRA Conference 2010 Conference Paper

Design, fabrication, and implementation of self-sealing suction cup arrays for grasping

Chad C. Kessens
Jaydev P. Desai

Suction cups have long been used as a means to grasp and manipulate objects. They enable active control of grasp, enhance grasp stability, and handle some objects such as large flat plates more easily than standard graspers. However, the application of suction cups to object manipulation has been confined to a relatively small, well-defined problem set. Their potential for grasping a large range of unknown objects remains relatively unexplored. This seems in part due to the complexity involved with the design and fabrication of various materials comprising the grasper as well as actuators used to enable grasping. This paper introduces the design of a suction cup that is “self-selecting. ” In other words, the suction cups comprising the grasper do not exert any suction force when the cup(s) are not in contact with the object, but instead exert a suction force only when they are in physical contact with the object. Since grasping is achieved purely by passive means, the cost and weight associated with individual sensors, valves, and/or actuators are essentially eliminated. Furthermore, the design permits the use of a central vacuum pump, thereby maximizing the suction force on an object and enabling some suction on surfaces that may prohibit tight seals. This paper presents the design, analysis, fabrication, and experimental results of such a “self-selecting” suction cup array.

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IROS Conference 2010 Conference Paper

Utilizing compliance to manipulate doors with unmodeled constraints

Chad C. Kessens
Joseph Rice
Daniel Carlton Smith
Stephen Biggs
Richard Garcia

Increasingly, robots are being applied to challenges in human environments such as soldier and disability assistance, household chores, and bomb disposal. To maximize a robot's capabilities within these dynamic and uncertain environments, robots must be able to manipulate objects with unknown constraints, including opening and closing doors, cabinets, and drawers. Practicality suggests that these tasks be done at or near human speed. A simple and low cost method is proposed to achieve these ends - utilizing joint compliance to resolve forces non-tangent to the path of travel. In this paper, joint compliance is achieved by means of a clutch mechanism located in line with the manipulator joint motors. When an object is to be moved, the motors are disengaged from the joints using the clutch, thus allowing the joints to move freely with the object while force is applied by the mobility platform. This enables the robot to move an object within its constraints without the need for a precise forcing vector, minimizing sensing needs as well as computation time. Other implementations of the technique are also possible, including use of inverse dynamics, back-drivable motors, and/or actively controlled slip clutches for gravity and friction compensation. The effectiveness and robustness of this approach are demonstrated through kinematic analysis, dynamic simulation, and physical experimentation on three differently sized doors and a drawer.

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