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About

Peiyao Shen is a robotics researcher whose work spans trajectory planning, motion optimization, and autonomous vehicle control. His most significant contributions lie in the domain of path-constrained trajectory planning for robotic systems, where he has tackled the long-standing challenge of simultaneously achieving time optimality and algorithmic completeness under real-world physical constraints such as torque, velocity, and acceleration limits. His 2018 paper on complete and time-optimal trajectory planning stands as his most influential work, accumulating 95 citations and offering both theoretical foundations and practical applications for reliable, efficient robot motion. Building on this, his 2020 work introduced a real-time acceleration-continuous planning algorithm with an elegant tradeoff between cruise and time-optimal motions, garnering 48 citations and advancing deployable solutions for industrial robotics. Shen's research extends beyond manipulator arms to encompass omnidirectional mobile robots, addressing multi-motor coordination and singularity avoidance, as well as cutting-edge work on flapping-wing aerial vehicles, where he applied differential flatness principles to trajectory generation and tracking control. His tree-search-based any-time planning approach further demonstrates his commitment to online, practical algorithmic solutions. Collectively, his work reflects a consistent drive to bridge theoretical rigor with real-world robotic deployment.