Papers
3
Total Citations
29
H-Index
3
About
Renhe Guan is a robotics researcher whose work centers on multi-robot coordination, perception-driven control, and human-machine interaction. His most impactful contribution, "Formation Tracking of Mobile Robots Under Obstacles Using Only an Active RGB-D Camera" (2023, 20 citations), addresses a critical limitation in swarm robotics: achieving leader-follower formation tracking with a single, low-cost RGB-D camera instead of the typical multi-sensor setups involving LiDAR. This innovation significantly reduces hardware complexity and cost, making formation control more accessible for real-world applications. Guan also advanced compliant robotics through "Adaptive impedance based force and position control for pneumatic compliant system" (2017, 6 citations), which improves robot safety and adaptability in human-machine interfaces and bionic systems. More recently, his work "A Distributed Optimization Approach for Collaborative Object Lifting Using Multiple Aerial Robots" (2023, 3 citations) reframes multi-robot transport as a distributed optimization problem, enabling efficient, decentralized coordination for aerial manipulation. Collectively, Guan’s research pushes the boundaries of sensor-efficient robotics, adaptive control, and distributed autonomy—key pillars for the next generation of collaborative and human-safe robotic systems.
Research Focus
Key Achievements
Top Papers
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