37 citations · 65 across the 11 of their papers we have counts for
12 papers
LightNav-0: Eliciting VLM Spatial Intelligence for Generalist Embodied Navigation
Shaoan Wang, Aocheng Luo, Fei Huang +17
Embodied navigation requires agents to translate heterogeneous goals and visual observations into actions across tasks, environments, and robot embodiments. Modern vision-language…
Light-Loco-Parkour: Versatile Perceptive Whole-Body Locomotion via Multi-Skill Distillation
Hongming Chen, Zhuoran Li, Hongxi Wang +9
Existing humanoid whole-body control systems still fall short of the way humans move through cluttered terrain: they either track expressive whole-body references without terrain g…
SE(2) Navigation Mesh
Shuyang Shi, Kaixian Qu, Changan Chen +3
Global navigation for ground robots in complex multi-level environments requires representations that accurately capture traversable regions while enabling efficient path planning.…
Collaborative Loco-Manipulation for Pick-and-Place Tasks with Dynamic Reward Curriculum
Tianxu An, Flavio De Vincenti, Yuntao Ma +2
We present a hierarchical RL pipeline for training one-armed legged robots to perform pick-and-place (P&P) tasks end-to-end -- from approaching the payload to releasing it at a tar…
Learning Accurate Whole-body Throwing with High-frequency Residual Policy and Pullback Tube Acceleration
Yuntao Ma, Yang Liu, Kaixian Qu +1
Throwing is a fundamental skill that enables robots to manipulate objects in ways that extend beyond the reach of their arms. We present a control framework that combines learning…
Learning coordinated badminton skills for legged manipulators
Yuntao Ma, Andrei Cramariuc, Farbod Farshidian +1
Coordinating the motion between lower and upper limbs and aligning limb control with perception are substantial challenges in robotics, particularly in dynamic environments. To thi…
Learning to Open and Traverse Doors with a Legged Manipulator
Mike Zhang, Yuntao Ma, Takahiro Miki +1
Using doors is a longstanding challenge in robotics and is of significant practical interest in giving robots greater access to human-centric spaces. The task is challenging due to…
IN-Sight: Interactive Navigation through Sight
Philipp Schoch, Fan Yang, Yuntao Ma +3
Current visual navigation systems often treat the environment as static, lacking the ability to adaptively interact with obstacles. This limitation leads to navigation failure when…
Learning Arm-Assisted Fall Damage Reduction and Recovery for Legged Mobile Manipulators
Yuntao Ma, Farbod Farshidian, Marco Hutter
Adaptive falling and recovery skills greatly extend the applicability of robot deployments. In the case of legged mobile manipulators, the robot arm could adaptively stop the fall…
Combining Learning-based Locomotion Policy with Model-based Manipulation for Legged Mobile Manipulators
Yuntao Ma, Farbod Farshidian, Takahiro Miki +2
Deep reinforcement learning produces robust locomotion policies for legged robots over challenging terrains. To date, few studies have leveraged model-based methods to combine thes…
Imitation Learning from MPC for Quadrupedal Multi-Gait Control
Alexander Reske, Jan Carius, Yuntao Ma +2
We present a learning algorithm for training a single policy that imitates multiple gaits of a walking robot. To achieve this, we use and extend MPC-Net, which is an Imitation Lear…
Preliminary Experimental Results of Context-Aware Teams of Multiple Autonomous Agents Operating under Constrained Communications
Jose Martinez-Lorenzo, Jeff Hudack, Yutao Jing +11
This work presents and experimentally test the framework used by our context-aware, distributed team of small Unmanned Aerial Systems (SUAS) capable of operating in real-time, in a…