12 papers
VertiAKD: Adaptive Off-Road Kinodynamics on Vertically Challenging Terrain
Tong Xu, Chenhui Pan, Francesco Cancelliere +1
Off-road mobility requires autonomous mobile robots to generalize across heterogeneous vehicle fleets and continuously changing terrain conditions. Existing cross-vehicle adaptatio…
CAR: Cross-Vehicle Kinodynamics Adaptation via Mobility Representation
Tong Xu, Chenhui Pan, Xuesu Xiao
Developing autonomous mobile robot systems typically requires either extensive, platform-specific data collection or relies on simplified abstractions, such as unicycle or bicycle…
VertiAdaptor: Online Kinodynamics Adaptation for Vertically Challenging Terrain
Tong Xu, Chenhui Pan, Aniket Datar +1
Autonomous driving in off-road environments presents significant challenges due to the dynamic and unpredictable nature of unstructured terrain. Traditional kinodynamic models ofte…
Verti-Arena: A Controllable and Standardized Indoor Testbed for Multi-Terrain Off-Road Autonomy
Haiyue Chen, Aniket Datar, Tong Xu +6
Off-road navigation is an important capability for mobile robots deployed in environments that are inaccessible or dangerous to humans, such as disaster response or planetary explo…
Adaptive Dynamics Planning for Robot Navigation
Yuanjie Lu, Mingyang Mao, Tong Xu +3
Autonomous robot navigation systems often rely on hierarchical planning, where global planners compute collision-free paths without considering dynamics, and local planners enforce…
VertiSelector: Automatic Curriculum Learning for Wheeled Mobility on Vertically Challenging Terrain
Tong Xu, Chenhui Pan, Xuesu Xiao
Reinforcement Learning (RL) has the potential to enable extreme off-road mobility by circumventing complex kinodynamic modeling, planning, and control by simulated end-to-end trial…