One of the key challenges in high-speed off-road navigation on ground vehicles is that the
kinodynamics of the vehicle-terrain interaction can differ dramatically depending on the …

When robots operate in real-world off-road environments with unstructured terrains, the
ability to adapt their navigational policy is critical for effective and safe navigation. However …

Robot data collected in complex real-world scenarios are often biased due to safety
concerns, human preferences, and mission or platform constraints. Consequently, robot …

We present VertiEncoder, a self-supervised representation learning approach for robot
mobility on vertically challenging terrain. Using the same pre-training process, VertiEncoder …

Autonomous navigation in unstructured environments is a challenging task due to the
complex and dynamic nature of robot-terrain interactions. Existing approaches often struggle …

Autonomous navigation in extreme mountainous terrains poses challenges due to the
presence of mobility-stressing elements and undulating surfaces, making it particularly …

Safety, security, and rescue missions typically occur in environments where unreliable
wireless communication impedes cooperative human and robot missions. A low-VHF band …

Mobile robots should be capable of planning cost-efficient paths for autonomous navigation.
Typically, the terrain and robot properties are subject to variations. For instance, properties …

In autonomous navigation settings, several quantities can be subject to variations. Terrain
properties such as friction coefficients may vary over time depending on the location of the …

Ground robots require the crucial capability of traversing unstructured and unprepared
terrains and avoiding obstacles to complete tasks in real-world robotics applications such as …