Hongyu Chu

Southwest University of Science and Technology

Papers

Total Citations

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About

Hongyu Chu is a researcher at the forefront of robotics and autonomous systems, with key contributions in visual servoing, robotic grasp detection, and 3D perception. Chu’s work addresses critical challenges in unmanned aerial vehicle (UAV) control, particularly through the application of deep reinforcement learning to overcome field-of-view constraints—a problem that has long hindered robust visual servoing in dynamic environments. This research, published in 2023, has already garnered 17 citations, reflecting its immediate impact on the field. In parallel, Chu developed DSC-GraspNet, a lightweight convolutional neural network that achieves a high-accuracy, low-latency balance for robotic grasp detection, also earning 17 citations. This innovation is pivotal for enabling intelligent, real-time autonomous manipulation in both industrial and virtual reality teleoperation settings. Earlier work includes a 3D perception and reconstruction system using a 2D laser scanner, demonstrating Chu’s versatility in sensor-based robotics, and a study on outdoor target tracking UAVs integrating KCF and face recognition. Chu’s research consistently bridges theoretical advances with practical deployment, making significant strides toward more capable, autonomous robotic systems.