Papers
1
Total Citations
8
H-Index
1
About
Keqi Luo is a researcher focused on the intersection of multiagent systems, stochastic control, and formation robotics. Their work addresses the challenge of coordinating complex, second-order multiagent systems—where agents control both velocity and acceleration—by leveraging stochastic control inputs rather than deterministic signals. In their highly cited 2023 paper, Luo introduced a novel framework that models a multiagent formation as a virtual structure tracking control system, using unicycle-type robots under a star-topology. By strategically injecting stochastic noise into the linear and rotational acceleration commands, they demonstrated that randomness can be harnessed to achieve precise, decentralized formation control. This approach offers a more robust and flexible alternative to traditional methods, particularly in uncertain or noisy environments. With 8 citations already, this work is gaining recognition for its theoretical depth and practical implications in swarm robotics and autonomous systems. Luo’s contributions are paving the way for more resilient and adaptive multi-robot coordination strategies, making their research essential reading for students and engineers working at the cutting edge of stochastic control and distributed robotics.
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