Daniel Rakita

Daniel Rakita is an Assistant Professor in the Department of Computer Science at Yale University. His research focuses on areas related to computer science, though specific details are not provided. Rakita's work contributes to the academic community through his teaching and scholarly activities within the department. His profile page provides further information about his research and academic contributions.

Daniel Rakita is a researcher at Yale University specializing in robotics, motion planning, optimization, machine learning, and spatial computing. His work focuses on developing methods for generating accurate and feasible robot arm motions, including optimization-based frameworks like RelaxedIK and Collisionik, which address collision avoidance and motion feasibility. He also explores shared control and teleoperation techniques for bimanual robot manipulation and remote telemanipulation in complex environments. His research emphasizes intent-expressive motion synthesis and the integration of human-robot interaction in virtual reality. Rakita's contributions include tools for benchmarking motion planning datasets and analyzing the effects of latency and speed delays on teleoperation performance.