Bounded haptic teleoperation of a quadruped robot's foot posture for sensing and manipulation
Guiyang Xin, Joshua Smith, David Rytz, Wouter Wolfslag, Hsiu-Chin Lin, and Michael Mistry

TL;DR
This paper introduces a control framework for haptic teleoperation of a quadruped robot's foot, enabling operator-guided exploration and manipulation with force feedback and safety constraints, demonstrated through experiments.
Contribution
It presents a hierarchical control scheme with force optimization and feedback mapping to ensure safe and effective teleoperation of a quadruped's foot posture.
Findings
Effective force estimation from trajectory errors.
Safe force mapping prevents slipping and falling.
Experimental validation shows framework efficiency.
Abstract
This paper presents a control framework to teleoperate a quadruped robot's foot for operator-guided haptic exploration of the environment. Since one leg of a quadruped robot typically only has 3 actuated degrees of freedom (DoFs), the torso is employed to assist foot posture control via a hierarchical whole-body controller. The foot and torso postures are controlled by two analytical Cartesian impedance controllers cascaded by a null space projector. The contact forces acting on supporting feet are optimized by quadratic programming (QP). The foot's Cartesian impedance controller may also estimate contact forces from trajectory tracking errors, and relay the force-feedback to the operator. A 7D haptic joystick, Sigma.7, transmits motion commands to the quadruped robot ANYmal, and renders the force feedback. Furthermore, the joystick's motion is bounded by mapping the foot's feasible…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRobotic Locomotion and Control · Prosthetics and Rehabilitation Robotics · Robot Manipulation and Learning
