1 citations · 2 across the 4 of their papers we have counts for
6 papers
ReCo: Response-Consistent Locomotion with Policy-Aware MPC for Legged Manipulation
Kuankuan Sima, Yichao Gao, Chenxi Gu +2
Continuous legged manipulation requires accurate end-effector tracking while the base keeps walking. Combining reinforcement learning (RL) with model predictive control (MPC) suits…
MacroNav: Multi-Task Context Representation Learning Enables Efficient Navigation in Unknown Environments
Kuankuan Sima, Longbin Tang, Zhenyu Yang +2
Autonomous navigation in unknown environments requires multi-scale spatial understanding that captures geometric details, topological connectivity, and global structure to support…
Centralized Reward Agent for Knowledge Sharing and Transfer in Multi-Task Reinforcement Learning
Haozhe Ma, Zhengding Luo, Thanh Vinh Vo +2
Reward shaping is effective in addressing the sparse-reward challenge in reinforcement learning (RL) by providing immediate feedback through auxiliary, informative rewards. Based o…
Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning
Haozhe Ma, Zhengding Luo, Thanh Vinh Vo +2
Reward shaping is a technique in reinforcement learning that addresses the sparse-reward problem by providing more frequent and informative rewards. We introduce a self-adaptive an…
Auto-Multilift: Distributed Learning and Control for Cooperative Load Transportation With Quadrotors
Bingheng Wang, Rui Huang, Lin Zhao
Designing motion control and planning algorithms for multilift systems remains challenging due to the complexities of dynamics, collision avoidance, actuator limits, and scalabilit…
MOMA-Force: Visual-Force Imitation for Real-World Mobile Manipulation
Taozheng Yang, Ya Jing, Hongtao Wu +5
In this paper, we present a novel method for mobile manipulators to perform multiple contact-rich manipulation tasks. While learning-based methods have the potential to generate ac…