Ravi Balasubramanian

Physical Human Interactive Guidance: Identifying Grasping Principles From Human-Planned Grasps

We present a novel and simple experimental method called physical human interactive guidance to study human-planned grasping. Instead of studying how the human uses his/her own biological hand or how a human teleoperates a robot hand in a grasping task, the method involves a human interacting physically with a robot arm and hand, carefully moving and guiding the robot into the grasping pose, while the robots configuration is recorded. Analysis of the grasps from this simple method has produced two interesting results. First, the grasps produced by this method perform better than grasps generated through a state-of-the-art automated grasp planner. Second, this method when combined with a detailed statistical analysis using a variety of grasp measures (physics-based heuristics considered critical for a good grasp) offered insights into how the human grasping method is similar or different from automated grasping synthesis techniques. Specifically, data from the physical human interactive guidance method showed that the human-planned grasping method provides grasps that are similar to grasps from a state-of-the-art automated grasp planner, but differed in one key aspect. The robot wrists were aligned with the objects principal axes in the human-planned grasps (termed low skewness in this paper), while the automated grasps used arbitrary wrist orientation. Preliminary tests show that grasps with low skewness were significantly more robust than grasps with high skewness (77-93%). We conclude with a detailed discussion of how the physical human interactive guidance method relates to existing methods to extract the human principles for physical interaction.

Human-guided grasp measures improve grasp robustness on physical robot

Humans are adept at grasping different objects robustly for different tasks. Robotic grasping has made significant progress, but still has not reached the level of robustness or versatility shown by human grasping. It would be useful to understand what parameters (called grasp measures) humans optimize as they grasp objects, how these grasp measures are varied for different tasks, and whether they can be applied to physical robots to improve their robustness and versatility. This paper demonstrates a new way to gather human-guided grasp measures from a human interacting haptically with a robotic arm and hand. The results revealed that a human-guided strategy provided grasps with higher robustness on a physical robot even under a vigorous shaking test (91%) when compared with a state-of-the-art automated grasp synthesis algorithm (77%). Furthermore, orthogonality of wrist orientation was identified as a key human-guided grasp measure, and using it along with an automated grasp synthesis algorithm improved the automated algorithms results dramatically (77% to 93%).

Human-robot Teaming for Rescue Missions: Team ViGIR's Approach to the 2013 DARPA Robotics Challenge Trials

Team ViGIR entered the 2013 DARPA Robotics Challenge DRC with a focus on developing software to enable an operator to guide a humanoid robot through the series of challenge tasks emulating disaster response scenarios. The overarching philosophy was to make our operators full team members and not just mere supervisors. We designed our operator control station OCS to allow multiple operators to request and share information as needed to maintain situational awareness under bandwidth constraints, while directing the robot to perform tasks with most planning and control taking place onboard the robot. Given the limited development time, we leveraged a number of open source libraries in both our onboard software and our OCS design; this included significant use of the robot operating system libraries and toolchain. This paper describes the high level approach, including the OCS design and major onboard components, and it presents our DRC Trials results. The paper concludes with a number of lessons learned that are being applied to the final phase of the competition and are useful for related projects as well.

Biological stiffness control strategies for the Anatomically Correct Testbed (ACT) hand

With the goal of developing biologically inspired manipulation strategies for an anthropomorphic hand, we investigated how the human central nervous system utilizes the hands redundant neuromusculoskeletal biomechanics to transition between conditions. Using a experiment protocol where subjects were asked to transit between control states with equal end-effector force but different stiffness requirements, we observed that (1) some subjects used the same muscle synergy for both conditions by maintaining the same synergy throughout the transition, and (2) other subjects used two different muscle synergies to execute two conditions by transiting from one synergy to another rapidly. We hypothesize that humans typically try to use the same muscle synergy to execute two tasks when it is possible to optimize on the simplicity and speed over energy. This is a different control strategy from the way robots have been controlled in the past, and it provides a new direction in controlling an anthropomorphic robotic hand.

Understanding variable moment arms for the index finger MCP joints through the ACT hand

Human levels of dexterity has not been duplicated in a robotic form to date. Dexterity is achieved in part due to the biomechanical structure, and in part due to the neural control of movement. An anatomically correct test-bed (ACT) hand has been constructed to investigate the importance and behavioral consequences of anatomical features and neural control strategies of the human hand. This paper focused on the role of the human handpsilas variable moment arm. System identification was conducted on the ACT index fingerpsilas two degrees of freedom at the metacarpal-phalange (MCP) joint to provide an understanding of, for the first time, how the moment arms vary with multiple joints moving simultaneously. The specific combination of nonlinear moment arms results in an increased ability to produce force at the fingertip for the same neural input when the fingerpsilas flexion and adduction angles increase (that is toward the middle of the hand). This preliminary work will lead to answering what biomechanical and neural functions are required to construct fully dexterous robotic and prosthetic hands in the future.

Task Performance is Prioritized Over Energy Reduction

The objective of this study was to characterize the temporal relationship between hand stiffness and task performance during adaptation to a brief contact task that required precision at the time of contact. The experiment required subjects to control the vertical position of a paddle on a computer display by grasping a robots instrumented handle, with the goal of intercepting a virtual ball within 1 mm from the paddle center. A force transient was applied to the hand immediately after the ball-paddle impact to estimate the intrinsic hand impedance. There were two main results: 1) more trials were required for a brief contact task to find a low-energy strategy when compared with tasks that received feedback through the entire movement trajectory and 2) when the whole course of adaptation is long for brief contact tasks, viscoelastic forces were increased to achieve the task goal before the energy reduction initiated. Also, as the accuracy requirement was increased by changing the gain between handle and paddle motion through visual amplification, peak stiffness increased and occurred later, indicating that higher energy strategies are used for longer when the tasks accuracy requirements were increased. These results indicated that task performance may be prioritized over energy reduction for a brief contact task.

Disturbance Response of Two-Link Underactuated Serial-Link Chains

In an attempt to improve the performance of underactuated robotic hands in grasping, we investigate the influence of the underlying coupling mechanism on the robustness of underactuated hands to external disturbance. The coupling mechanisms used in underactuated mechanisms can be divided into two main classes based on the self-adaptive transmission used to route actuation to the degrees of freedom, namely single-acting and double-acting transmissions. The kinematic coupling constraint is always active in double-acting mechanisms, while there are specific combinations of external disturbances and mechanism parameters that render the constraint inactive in single-acting mechanisms. This paper identifies unique behaviors in terms of mechanism reconfiguration and variation in grasping contact forces that result from the underactuated hand’s response to external disturbance forces and show that these behaviors are a function of the coupling mechanism, actuation mode, and contact constraints. We then present an analysis of how these behaviors influence grasping ability of the hand and discuss implications for underactuated hand design and operation. [DOI: 10.1115/1.4006279]

Acquiring Variable Moment Arms for Index Finger Using a Robotic Testbed

Human level of dexterity has not been duplicated in a robotic form to date. Dexterity is achieved in part due to the biomechanical structure of the human body and in part due to the neural control of movement. We have developed an anatomically correct testbed (ACT) hand to investigate the importance and behavioral consequences of anatomical features and neural control strategies of the human hand. One of the critical aspects of understanding dexterity is the analysis of the relationships between the hand muscle movements and joint movements, defined by the moment arms of the muscles. It is known that the moment arms for the hand muscles are configuration-dependent and vary substantially with change in posture. This paper presents a methodology for determining continuous variations in the moment arms with respect to multiple joints moving simultaneously. To determine variations in the moment arms of the ACT hand index finger muscles, we employed a nonparametric regression method called Gaussian processes (GPs). GPs give a functional mapping between the joint angles and muscle excursions, and the gradients of these mappings are the muscle moment arms. We compared the moment arm relationships of the ACT hand with those determined from the available cadaver data. We present the implications of the determination of variable moment arms toward understanding of the biomechanical properties of the human hand and for the neuromuscular control for the ACT hand index finger movements.

EXTERNAL DISTURBANCES AND COUPLING MECHANISMS IN UNDERACTUATED HANDS

With the goal of improving the performance of underactuated robotic hands in grasping, we investigate the influence of the underlying coupling mechanism on the robustness of underactuated hands to external disturbance. This paper identifies unique behaviors in the hand’s response as a function of the coupling mechanism and the actuation mode the hand is operated in. Specifically, we show that in conditions when the actuator position is fixed, hands with single-acting mechanisms exhibit a bimodal behavior in contrast to hands with double-acting mechanisms that exhibit a unimodal behavior. We then present an analysis of how these behaviors influence grasping capability of the hand and then discuss implications for underactuated hand design and operation.Copyright

Legless locomotion for legged robots

We propose a locomotion technique for a legged robot that is high-centered, i.e., a robot stuck on a block with its legs dangling in air. By using its legs as reaction masses, the robot might be able to rock and roll on its stomach and incrementally move forward off the block, a form of legless locomotion using halteres. With locomotion of high-centered robots using body attitude oscillations as motivation, this paper focuses on studying the interplay between leg motions and body roll-pitch-yaw dynamics. We present results from simulation of two simplified models in which body motion is restricted to the roll and roll-yaw space respectively.