arXiv subjects

Junheng Li

Publications and source records attributed to Junheng Li.

22 records · Page 2Linked to original sources

arXiv2023

Multi-contact MPC for Dynamic Loco-manipulation on Humanoid Robots

This paper presents a novel method to control humanoid robot dynamic loco-manipulation with multiple contact modes via multi-contact Model Predictive Control (MPC) framework. The proposed framework includes a multi-contact dynamics model capable of capturing various contact modes in loco-manipulation, such as hand-object contact and foot-ground contacts. Our proposed dynamics model represents the object dynamics as an external force acting on the system, which simplifies the model and makes it feasible for solving the MPC problem. In numerical validations, our multi-contact MPC framework only needs contact timings of each task and desired states to give MPC the knowledge of changes in contact modes in the prediction horizons in loco-manipulation. The proposed framework can control the humanoid robot to complete multi-tasks dynamic loco-manipulation applications such as efficiently picking up and dropping off objects while turning and walking.

cs.RO↗

arXiv2022

Dynamic Walking of Bipedal Robots on Uneven Stepping Stones via Adaptive-frequency MPC

This paper presents a novel Adaptive-frequency MPC framework for bipedal locomotion over terrain with uneven stepping stones. In detail, we intend to achieve adaptive foot placement and gait period for bipedal periodic walking gait with this MPC, in order to traverse terrain with discontinuities without slowing down. We pair this adaptive-frequency MPC with a kino-dynamics trajectory optimization for optimal gait periods, center of mass (CoM) trajectory, and foot placements. We use whole-body control (WBC) along with adaptive-frequency MPC to track the optimal trajectories from the offline optimization. In numerical validations, our adaptive-frequency MPC framework with optimization has shown advantages over fixed-frequency MPC. The proposed framework can control the bipedal robot to traverse through uneven stepping stone terrains with perturbed stone heights, widths, and surface shapes while maintaining an average speed of 1.5 m/s.

cs.RO↗

arXiv2022

Balancing Control and Pose Optimization for Wheel-legged Robots Navigating High Obstacles

In this paper, we propose a novel approach on controlling wheel-legged quadrupedal robots using pose optimization and force control via quadratic programming (QP). Our method allows the robot to leverage the whole-body motion and the wheel actuation to roll over high obstacles while keeping the wheel torques to navigate the terrain while keeping the wheel traction and balancing the robot body. In detail, we first present a linear rigid body dynamics with wheels that can be used for real-time balancing control of wheel-legged robots. We then introduce an effective pose optimization method for wheel-legged robot's locomotion over steep ramp and stair terrains. The pose optimization solves for optimal poses to enhance stability and enforce collision-fee constraints for the rolling motion over stair terrain. Experimental validation on the real robot demonstrated the capability of rolling up on a 0.36 m obstacle. The robot can also successfully roll up and down multiple stairs without lifting its legs or having collision with the terrain.

cs.RO↗

arXiv2021

Force-and-moment-based Model Predictive Control for Achieving Highly Dynamic Locomotion on Bipedal Robots

In this paper, we propose a novel framework on force-and-moment-based Model Predictive Control (MPC) for dynamic legged robots. Specifically, we present a formulation of MPC designed for 10 degree-of-freedom (DoF) bipedal robots using simplified rigid body dynamics with input forces and moments. This MPC controller will calculate the optimal inputs applied to the robot, including 3-D forces and 2-D moments at each foot. These desired inputs will then be generated by mapping these forces and moments to motor torques of 5 actuators on each leg. We evaluate our proposed control design on physical simulation of a 10 degree-of-freedom (DoF) bipedal robot. The robot can achieve fast walking speed up to 1.6 m/s on rough terrain, with accurate velocity tracking. With the same control framework, our proposed approach can achieve a wide range of dynamic motions including walking, hopping, and running using the same set of control parameters.

cs.RO↗