GRASP

Multi-robot coordination and cooperation are critical behaviors that improve team performance and enable new tasks in application areas like autonomous construction, agriculture, and extended operation in large unknown regions. This dissertation examines these behaviors in the context of the multi-robot resource allocation problem, where robots must be allocated to regions of demand. In particular, we […]

Legged robots, robotic manipulators, and their combined embodiment as humanoid robots have received considerable attention across both academia and industry. However, with few notable exceptions, state-of-the-art demonstrations are significantly less dynamic than their biological counterparts. A considerable challenge towards achieving more dynamic robots lies within controlling contact interactions with their environment. Legged robots undergoing impacts […]

Autonomous aerial robots today are capable of safely navigating through cluttered, GPS-denied environments while constructing an accurate map that captures geometric features such as points, lines, and planes. Such maps are crucial for low-level planning and obstacle avoidance. However, beyond offering details on the density, layout, and dimensions of the environment, these maps provide limited […]

Despite substantial progress in robotics, achieving human-like manipulation remains a significant challenge. Existing robotic systems typically leverage human-inspired sensory modalities: vision, touch, and proprioception. However, these modalities are historically studied and integrated in isolation, leading to limited performance in complex real-world tasks that require sensing across multiple modalities for robust generalization. As a result, robots […]