7 papers
Verti-Bench: A General and Scalable Off-Road Mobility Benchmark for Vertically Challenging Terrain
Tong Xu, Chenhui Pan, Madhan B. Rao +4
Recent advancement in off-road autonomy has shown promises in deploying autonomous mobile robots in outdoor off-road environments. Encouraging results have been reported from both…
Reinforcement Learning for Wheeled Mobility on Vertically Challenging Terrain
Tong Xu, Chenhui Pan, Xuesu Xiao
Off-road navigation on vertically challenging terrain, involving steep slopes and rugged boulders, presents significant challenges for wheeled robots both at the planning level to…
M2P2: A Multi-Modal Passive Perception Dataset for Off-Road Mobility in Extreme Low-Light Conditions
Aniket Datar, Anuj Pokhrel, Mohammad Nazeri +8
Long-duration, off-road, autonomous missions require robots to continuously perceive their surroundings regardless of the ambient lighting conditions. Most existing autonomy system…
Traverse the Non-Traversable: Estimating Traversability for Wheeled Mobility on Vertically Challenging Terrain
Chenhui Pan, Aniket Datar, Anuj Pokhrel +3
Most traversability estimation techniques divide off-road terrain into traversable (e.g., pavement, gravel, and grass) and non-traversable (e.g., boulders, vegetation, and ditches)…
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…
VertiCoder: Self-Supervised Kinodynamic Representation Learning on Vertically Challenging Terrain
Mohammad Nazeri, Aniket Datar, Anuj Pokhrel +3
We present VertiCoder, a self-supervised representation learning approach for robot mobility on vertically challenging terrain. Using the same pre-training process, VertiCoder can…