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Chenkun Qi

7 accepted papers

2026

MLM: Learning Multi-Task Loco-Manipulation Whole-Body Control for Quadruped Robot With Arm

RA-L 2026

Whole-body loco-manipulation for quadruped robots with arms remains a challenging problem, particularly in achieving multi-task control. To address this, we propose MLM, a reinforcement learning framework driven by both real-world and simulation data. It enables a six-DoF robotic arm–equipped quadru

Cited by 4SourceScholar
2026

PPL: Point Cloud Supervised Proprioceptive Locomotion Reinforcement Learning for Legged Robots in Crawl Spaces

RA-L 2026

Legged locomotion in constrained spaces (called crawl spaces) is challenging. In crawl spaces, current proprioceptive locomotion learning methods are difficult to achieve traverse because only ground features are inferred. In this study, a point cloud supervised RL framework for proprioceptive locom

Cited by 1SourceScholar
2025

Learning Natural and Robust Hexapod Locomotion over Complex Terrains via Motion Priors based on Deep Reinforcement Learning

IROS 2025

Multi-legged robots offer enhanced stability to navigate complex terrains with their multiple legs interacting with the environment. However, how to effectively coordinate the multiple legs in a larger action exploration space to generate natural and robust movements is a key issue. In this paper, w

Cited by 0SourceScholar
2023

Learning-Based Distortion Compensation for a Hybrid Simulator of Space Docking

RA-L 2023

By effectively utilizing the fidelity of a physical simulation and the flexibility of a numerical simulation, the hybrid simulation is applicable to test the complicated docking contact process of various kinds of spacecraft. However, the hybrid simulation of space docking often has a divergence or

Cited by 5SourceScholar
2021

Design and soft-landing control of a six-legged mobile repetitive lander for lunar exploration

ICRA 2021poster

The autonomous robots consisting of an immovable lander and a rover are widely deployed to explore extraterrestrial planets. However, these robots have two main limitations: (1) the separate design for lander and rover respectively results in heavy mass and big volume of the whole system, which incr…

Cited by 8SourceScholar
2021

Stair Climbing Capability-Based Dimensional Synthesis for the Multi-legged Robot

ICRA 2021poster

Staircase is a typical obstacle for the legged robot to overcome in buildings. This paper studies the stair climbing capability-based dimensional synthesis for a hexapod legged robot, i.e., exploring how to determine the leg length and the longitudinal body length concerning the target staircase in…

Cited by 10SourceScholar