Zhixiang Li
Papers
2
Total Citations
5
H-Index
2
About
Zhixiang Li is a robotics researcher focused on advancing the intelligence and adaptability of service and mobile robotic systems. Their primary research areas include computer vision, deep learning for object recognition, and reconfigurable robot design. Li’s major contributions center on improving the autonomy and precision of robots in unstructured environments. In their highly cited 2024 work on target recognition and grasping, Li proposed a novel method using the YOLOv8 deep learning algorithm to enable dual-arm cooperative mobile robots to accurately identify and grasp household objects, directly addressing common challenges in service robotics such as low recognition accuracy and insufficient stability. This work has already garnered 3 citations, signaling its relevance to the field. Additionally, Li developed an omni-directional mobile reconfigurable robot (OMRR) featuring a symmetrical McNamum wheel chassis and Arduino-based control, which provides stable, balanced traction for versatile movement. This design, detailed in a 2024 paper with 2 citations, demonstrates Li’s skill in integrating mechanical design with embedded systems. Through these achievements, Zhixiang Li is contributing practical, vision-driven solutions that bring robots closer to reliable, everyday home assistance.
Research Focus
Key Achievements
Top Papers
- 1
- 2