Abstract: Robot dexterity remains an open challenge in robotics that has the potential to transform manufacturing, healthcare, and daily life. Robots that safely and robustly interact with unstructured environments must combine compliant hardware with models and planners that tolerate uncertainty. Additionally, if robust robot dexterity is to be realized outside of research labs, it must [...]

Abstract Autonomous robots should maintain resilient spatial perception despite sensor degradation. Humans preserve spatial awareness when moving between well-lit and dark spaces or when vision is partially occluded. Neuroscience studies suggest this robustness relies in part on a proprioception-first sensory hierarchy: the vestibular system provides continuous inertial reference signals, while vision supplies corrective updates that [...]

Abstract: Uncrewed Aerial Vehicles (UAVs) have attracted significant attention in applications such as inspection and maintenance. Many of these tasks require aerial robots to physically interact with the environment, motivating the emerging field of aerial manipulation. However, most existing approaches focus on a single task with specialized hardware and control strategies, limiting their ability to [...]

Abstract:  Robots, and autonomous systems in general, are becoming increasingly advancing beyond traditional functions. This can potentially facilitate the mismatch between human expectations of system behaviors during interaction, especially when the systems behave unexpectedly. Unexpected system behaviors could induce negative emotional responses in humans, which not all systems have the capability of recognizing and detecting [...]

Date: 30th March 2026 Time: 10:00 a.m. (ET) Location: NSH 3305 Zoom: Link Type: Ph.D. Thesis Defense Who: Brian Yang Title: A Language-Guided Generative Data Engine for Autonomous Driving   Abstract: Autonomous driving systems struggle with the long tail of rare and safety-critical scenarios that are sparsely represented in real-world data. While recent learning-based planners perform well on common situations, their reliability [...]

Who: Ananya Rao Date: Friday, April 3rd Time: 10 AM ET Location: NSH 3305 Zoom Link Meeting ID: 949 1271 6317 Passcode: 809985 Title: Spectral-Based Coordination of Heterogeneous Multi-Agent Teams for Information Gathering Abstract: Extreme environments, such as those encountered in planetary exploration or disaster response, present complex, time-sensitive tasks with significant uncertainty. In such settings, heterogeneous [...]