17 citations · 27 across the 8 of their papers we have counts for
8 papers
MagRobot:An Open Simulator for Magnetically Navigated Robots
Heng Wang, Haoyu Song, Jiatao Zheng +2
Magnetic navigation systems, including magnetic tracking systems and magnetic actuation systems, have shown great potential for occlusion-free localization and remote control of in…
Learning Differentiable Tensegrity Dynamics using Graph Neural Networks
Nelson Chen, Kun Wang, William R. Johnson +3
Tensegrity robots are composed of rigid struts and flexible cables. They constitute an emerging class of hybrid rigid-soft robotic systems and are promising systems for a wide arra…
A Recurrent Differentiable Engine for Modeling Tensegrity Robots Trainable with Low-Frequency Data
Kun Wang, Mridul Aanjaneya, Kostas Bekris
Tensegrity robots, composed of rigid rods and flexible cables, are difficult to accurately model and control given the presence of complex dynamics and high number of DoFs. Differe…
Elongation of Curvature-Bounded Path
Zheng Chen, Kun Wang, Yang Lu
The paper is concerned with elongating the shortest curvature-bounded path between two oriented points to an expected length. The elongation of curvature-bounded paths to an expect…
Spring-Rod System Identification via Differentiable Physics Engine
Kun Wang, Mridul Aanjaneya, Kostas Bekris
We propose a novel differentiable physics engine for system identification of complex spring-rod assemblies. Unlike black-box data-driven methods for learning the evolution of a dy…
Sim2Sim Evaluation of a Novel Data-Efficient Differentiable Physics Engine for Tensegrity Robots
Kun Wang, Mridul Aanjaneya, Kostas Bekris
Learning policies in simulation is promising for reducing human effort when training robot controllers. This is especially true for soft robots that are more adaptive and safe but…