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Shiliang Guo

4 accepted papers

2025

Cooperative Bearing-Only Target Pursuit via Multiagent Reinforcement Learning: Design and Experiment

IROS 2025

This paper addresses the multi-robot pursuit problem for an unknown target, encompassing both target state estimation and pursuit control. First, in state estimation, we focus on using only bearing information, as it is readily available from vision sensors and effective for small, distant targets.

Cited by 2SourceScholar
2025

EvDetMAV: Generalized MAV Detection From Moving Event Cameras

RA-L 2025

Existing micro aerial vehicle (MAV) detection methods mainly rely on the target's appearance features in RGB images, whose diversity makes it difficult to achieve generalized MAV detection. We notice that different types of MAVs share the same distinctive features in event streams due to their high-

Cited by 4SourcecodeScholar
2025

TACO: General Acrobatic Flight Control via Target-and-Command-Oriented Reinforcement Learning

IROS 2025

Although acrobatic flight control has been studied extensively, one key limitation of the existing methods is that they are usually restricted to specific maneuver tasks and cannot change flight pattern parameters online. In this work, we propose a target-and-command-oriented reinforcement learning

Cited by 3SourcecodeScholar