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Adaptive Fingers Coordination for Robust Grasp and In-Hand Manipulation Under Disturbances and Unknown Dynamics

Aude Billard, Farshad Khadivar

We present a control framework for achieving a robust object grasp and manipulation in hand. In-hand manipulation remains a demanding task as the object is never stable and task success relies on carefully synchronizing the fingers' dynamics. Indeed, fingers must simultaneously generate motion while maintaining contact with the object and, by staying within the hand's frame, ensuring that the object remains manipulable. These challenges are exacerbated once the hand gets disturbed or when the internal dynamics of the manipulated object are unknown, such as when it is filled with liquid moving during manipulation. We present a control strategy based on coupled dynamical systems (DSs), whereby the fingers move in synchronization using an intermediate dynamics responsible for coordinating fingers. To adapt to changes in forces due to model uncertainties and unexpected disturbances, we employ an adaptive torque-controller combined with a joint impedance regulator that guarantees high tracking accuracy while adapting to dynamic changes. We validate the approach in multiple experiments on 16-degrees-of-freedom robotic hand grasping and manipulating objects with different mass properties, e.g., uneven or varying mass distribution in a glass half-filled with water. We show that the robot can compensate for disturbances generated by internal dynamics and external perturbations. Additionally, we showcase how our controller, in conjunction with learning from human demonstration, provides a robust solution for more complicated manipulations such as finger gaiting.

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Bimanual dynamic grabbing and tossing of objects onto a moving target

Aude Billard, Michael Bombile Bosongo

Bimanual grabbing and tossing of packages onto trays or conveyor belts remains a human activity in the industry. For robots, such a dynamic task requires coordination between two arms and fast adaptation abilities when the tossing target is moving and subject to perturbations. Thus, this paper proposes a control framework that enables a bimanual robotic system to grab and toss objects onto a moving target. We develop a mixed learning-optimization method that computes the tossing parameters necessary to achieve accurate tossing tasks. Hence, we learn an inverse throwing map (a closed-form solution of the inverse non-linear throwing problem) that provides minimum release velocities of the object for given relative release positions. This map is embedded into a kinematics-based bi-level optimization that determines the associated feasible release states (positions and velocities) of the dual-arm robot. Additionally, we propose a closed-form modeling approach of the robot’s tossable workspace (set of all positions reachable by an object if tossed by the robot) and use the model to predict intercept or landing locations that yield high probabilities of task success. Furthermore, we employ dynamical systems to generate the coordinated motion of the dual-arm system and design an adaptation strategy to ensure robustness of the interception in the face of target’s perturbations in speed or location. Finally, we validate experimentally the framework on two 7-DoF robotic arms. We demonstrate the accuracy and robustness of the proposed approach. We also show its speed and energy advantages when compared to the traditional pick-and-place strategy.

2023

Enabling four-arm laparoscopic surgery by controlling two robotic assistants via haptic foot interfaces

Walid Amanhoud, Aude Billard, Mohamed Bouri, Jacob Hernandez Sanchez

Robotic surgery is a promising direction to improve surgeons and assistants’ daily life with respect to conventional surgery. In this work, we propose solo laparoscopic surgery in which two robotic arms, controlled via haptic foot interfaces, assist the task of the hands. Such a system opens the door for simultaneous control of four laparoscopic tools by the same user. Each hand controls a manipulative tool while a foot controls an endoscope/camera and another controls an actuated gripper. In this scenario, the surgeon and robots need to work collaboratively within a concurrent workspace, while meeting the precision demands of surgery. To this end, we propose a control framework for the robotic arms that deals with all the task- and safety-related constraints. Furthermore, to ease the control through the feet, two assistance modalities are proposed: adaptive visual tracking of the laparoscopic instruments with the camera and grasping assistance for the gripper. A user study is conducted on twelve subjects to highlight the ease of use of the system and to evaluate the relevance of the proposed shared control strategies. The results confirm the feasibility of four-arm surgical-like tasks without extensive training in tasks that involve visual-tracking and manipulation goals for the feet, as well as coordination with both hands. Moreover, our study characterizes and motivates the use of robotic assistance for reducing task load, improving performance, increasing fluency, and eliciting higher coordination during four-arm laparoscopic tasks.

2023