8 accepted papers
Long-duration, off-road, autonomous missions require robots to continuously perceive their surroundings regardless of the ambient lighting conditions. Most existing autonomy systems heavily rely on active sensing, e.g., LiDAR, RADAR, and Time-of-Flight sensors, or use (stereo) visible light imaging
As mobile robots become increasingly common in human-centric environments, social navigation—adhering to unwritten social norms rather than merely avoiding pedestrians—has drawn growing attention. Existing methods, from hand-crafted techniques to learning-based approaches, often overlook the nuanced
We present Verticoder, a self-supervised representation learning approach for robot mobility on vertically challenging terrain. Using the same pre-training process, Ver-ticodercan handle four different downstream tasks, in-cluding forward kinodynamics learning, inverse kinodynamics learning, behavio
While the workspace of traditional ground vehicles is usually assumed to be in a 2D plane, i.e., <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathbb {SE}(2)$</tex-math></inline-formula>, such an assumption may
Wheeled robots have recently demonstrated superior mechanical capability to traverse vertically challenging terrain (e.g., extremely rugged boulders comparable in size to the vehicles themselves). Negotiating such terrain introduces significant variations of vehicle pose in all six Degrees-of-Freedo…
Most conventional wheeled robots can only move in flat environments and simply divide their planar workspaces into free spaces and obstacles. Deeming obstacles as non-traversable significantly limits wheeled robots’ mobility in real-world, extremely rugged, off-road environments, where part of the t…
Humans excel at efficiently navigating through crowds without collision by focusing on specific visual regions relevant to navigation. However, most robotic visual navigation methods rely on deep learning models pre-trained on vision tasks, which prioritize salient objects—not necessarily relevant t…
Humans are well-adept at navigating public spaces shared with others, where current autonomous mobile robots still struggle: while safely and efficiently reaching their goals, humans communicate their intentions and conform to unwritten social norms on a daily basis; conversely, robots become clumsy…