Abstract: Model predictive control (MPC) is a powerful tool for controlling highly dynamic robotic systems subject to complex constraints. However, it is computationally expensive and often requires a large memory footprint. Larger robotic systems are capable of carrying and powering sophisticated computational hardware onboard. On the other hand, smaller robots typically have faster dynamics that […]

Abstract: Legged robot hardware has become more accessible in the last ten years. However, there is still a dearth of low-cost hardware platforms that are open-source and easy to build. With recent developments in accessible manufacturing methods, such as 3D printing, it has become possible to design and manufacture parts without relying on precision machining. […]

Abstract: Robotic assistance is used today in a variety of surgeries as a means of precise, dexterous, and minimally-invasive manipulation. However, practical use in microsurgical environments such as vitreoretinal surgery remains a challenge for the most common mechanically-grounded robotic platforms. Microsurgery requires micron-level accuracy and the ability to manipulate with interaction forces in millinewtons. Vitreoretinal […]

Abstract: Whether it is in sorting defects from grain in an agricultural setting, ore from tailings in a mine, or letters in a postal system, the sorting of bulk material has long been a crucial aspect of human industry.  Today, in the face of dwindling natural resource deposits and accelerating climate change, a particularly important […]

Abstract: Multi-agent reinforcement learning presents unique hurdles such as the non-stationary problem beyond single-agent reinforcement learning that makes learning effective decentralized cooperative policies using an agent's local state extremely challenging. Effective communication to share information and coordinate is vital for agents to work together and solve cooperative tasks, as the ubiquitous evidence of communication in […]

Abstract: The ability to identify important objects in a complex and dynamic driving environment can help assistive driving systems alert drivers. These assistance systems also require a model of the drivers' situational awareness (SA) (what aspects of the scene they are already aware of) to avoid unnecessary alerts. This thesis builds towards such intelligent driving [...]

Abstract: Autonomous robot navigation in off-road environments currently presents a number of challenges. The lack of structure makes it difficult to handcraft geometry-based heuristics that are robust to the diverse set of scenarios the robot might encounter. Many of the learned methods that work well in urban scenarios require massive amounts of hand-labeled data, but [...]