8 papers
A Deployable Bio-inspired Compliant Leg Design for Enhanced Leaping in Quadruped Robots
Yiyang Chen, Yuxin Liu, Jinzheng Zhou +4
Quadruped robots are becoming increasingly essential for various applications, including industrial inspection and catastrophe search and rescue. These scenarios require robots to…
Sampling Strategy Design for Model Predictive Path Integral Control on Legged Robot Locomotion
Chuyuan Tao, Fanxin Wang, Haolong Jiang +3
Model Predictive Path Integral (MPPI) control has emerged as a powerful sampling-based optimal control method for complex, nonlinear, and high-dimensional systems. However, directl…
Needle Biopsy And Fiber-Optic Compatible Robotic Insertion Platform
Fanxin Wang, Yikun Cheng, Chuyuan Tao +2
Tissue biopsy is the gold standard for diagnosing many diseases, involving the extraction of diseased tissue for histopathology analysis by expert pathologists. However, this proce…
DBaS-Log-MPPI: Efficient and Safe Trajectory Optimization via Barrier States
Fanxin Wang, Haolong Jiang, Chuyuan Tao +2
Optimizing trajectory costs for nonlinear control systems remains a significant challenge. Model Predictive Control (MPC), particularly sampling-based approaches such as the Model…
MPPI-DBaS: Safe Trajectory Optimization with Adaptive Exploration
Fanxin Wang, Yikun Cheng, Chuyuan Tao
In trajectory optimization, Model Predictive Path Integral (MPPI) control is a sampling-based Model Predictive Control (MPC) framework that generates optimal inputs by efficiently…
Transformer Based Tissue Classification in Robotic Needle Biopsy
Fanxin Wang, Yikun Cheng, Sudipta S Mukherjee +2
Image-guided minimally invasive robotic surgery is commonly employed for tasks such as needle biopsies or localized therapies. However, the nonlinear deformation of various tissue…
An Optimization-Based Planner with B-spline Parameterized Continuous-Time Reference Signals
Chuyuan Tao, Sheng Cheng, Yang Zhao +2
For the cascaded planning and control modules implemented for robot navigation, the frequency gap between the planner and controller has received limited attention. In this study,…
Improving the Robustness of Reinforcement Learning Policies with Adaptive Control
Y. Cheng, P. Zhao, F. Wang +2
A reinforcement learning (RL) control policy could fail in a new/perturbed environment that is different from the training environment, due to the presence of dynamic variations. F…