23 papers
PRIMAL3: Pathfinding via Reinforcement and Imitation Multi-Agent Learning - Leveraging LaCAM3
Chengyang He, Tanishq Duhan, Gadiel Sznaier Camps +6
We present PRIMAL3, an ultra-large-scale learning-based framework for multi-agent pathfinding (MAPF) that integrates reinforcement learning, topology-aware communication, LaCAM3-gu…
KiVi: Kinesthetic-Visuospatial Integration for Dynamic and Safe Egocentric Legged Locomotion
Peizhuo Li, Hongyi Li, Yuxuan Ma +8
Vision-based locomotion has shown great promise in enabling legged robots to perceive and adapt to complex environments. However, visual information is inherently fragile, being vu…
APEX: Action Priors Enable Efficient Exploration for Robust Motion Tracking on Legged Robots
Shivam Sood, Laukik Nakhwa, Sun Ge +7
Learning natural, animal-like locomotion from demonstrations has become a core paradigm in legged robotics. While motion tracking can reproduce reference gaits, many approaches sti…
TAGA: Terrain-aware Active Gaze Learning for Generalizable Agile Humanoid Locomotion
Peizhuo Li, Hongyi Li, Mingfeng Fan +9
Agile humanoid locomotion across diverse challenging terrain demands both wide perceptual coverage and precise local geometry understanding. Motivated by the way humans selectively…
HeLoM: Hierarchical Learning for Whole-Body Loco-Manipulation by a Hexapod Robot
Xinrong Yang, Peizhuo Li, Hongyi Li +8
In nature, animals often need to move/manipulate objects comparable in weight/size to their own bodies. Compared to grasping and carrying, pushing provides a more straightforward a…
ORION: Option-Regularized Deep Reinforcement Learning for Cooperative Multi-Agent Online Navigation
Shizhe Zhang, Jingsong Liang, Zhitao Zhou +6
Existing methods for multi-agent navigation typically assume fully known environments, offering limited support for partially known scenarios with outdated or imperfect prior maps,…