36 citations · 47 across the 4 of their papers we have counts for
4 papers · 1 filter
Deep Reinforcement Learning for Tensegrity Robot Locomotion
Marvin Zhang, Xinyang Geng, Jonathan Bruce +5
Tensegrity robots, composed of rigid rods connected by elastic cables, have a number of unique properties that make them appealing for use as planetary exploration rovers. However,…
A Bio-Inspired Tensegrity Manipulator with Multi-DOF, Structurally Compliant Joints
Steven Lessard, Dennis Castro, William Asper +5
Most traditional robotic mechanisms feature inelastic joints that are unable to robustly handle large deformations and off-axis moments. As a result, the applied loads are transfer…
A light-weight, multi-axis compliant tensegrity joint
Steven Lessard, Jonathan Bruce, Erik Jung +3
In this paper, we present a light-weight, multi- axis compliant tenegrity joint that is biologically inspired by the human elbow. This tensegrity elbow actuates by shortening and l…
State Estimation for Tensegrity Robots
Ken Caluwaerts, Jonathan Bruce, Jeffrey M. Friesen +1
Tensegrity robots are a class of compliant robots that have many desirable traits when designing mass efficient systems that must interact with uncertain environments. Various prom…