Kai Chuen Tan

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About

Kai Chuen Tan is a robotics researcher specializing in cooperative multi-agent systems, motion planning, and task allocation for unconventional robotic platforms. His work focuses on enabling teams of hybrid-mobility rovers—capable of both ground travel and jumping—to efficiently navigate complex, obstacle-rich environments. Tan’s major contributions include developing novel algorithms that address the multiple traveling salesman problem (mTSP) with obstacles, where each unmanned ground vehicle (UGV) can switch between driving and jumping modes to improve traversability. His 2020 paper on motion planning and task allocation for a jumping rover team (7 citations) introduces a cooperative framework that optimizes route efficiency for heterogeneous robot teams. In his 2022 follow-up work (2 citations), Tan extends this concept by incorporating a mobile charging station, allowing jumping rovers with distinct energy profiles to sustain long-duration multi-waypoint missions. This integration of energy-aware planning with hybrid locomotion represents a significant step toward persistent autonomous exploration in challenging terrains. Tan’s research is particularly relevant for planetary exploration, disaster response, and agricultural monitoring, where traditional wheeled robots struggle. His work demonstrates a creative synthesis of combinatorial optimization and biologically inspired locomotion, positioning him as an emerging voice in field robotics.