Weijia Wang

University of Hong Kong, Xi'an Aeronautical University

Papers

Total Citations

H-Index

About

Weijia Wang’s research focuses on humanoid robotics, autonomous manipulation, and evolutionary robotics, with a particular emphasis on enabling robots to perform complex, real-world tasks with minimal human intervention. His most notable contribution is the development of an integrated valve-turning skill for the Atlas humanoid robot, which combines autonomous valve identification, motion planning, biped locomotion, and compliant manipulation in a single, supervisory-controlled framework. This work, published in 2014 and cited 8 times, demonstrates a practical step toward deploying humanoid robots in hazardous environments such as disaster response or industrial maintenance. Wang also explores the use of information theory in evolutionary robotics, proposing a hierarchic entropy measure to quantify behavioral diversity in robot controllers. This approach, introduced in a 2016 paper with 4 citations, offers a more nuanced fitness function for evolving complex, adaptive behaviors. While his citation counts are modest, Wang’s work is notable for its integration of perception, planning, and control on a state-of-the-art humanoid platform, and for pushing the boundaries of autonomous robot operation in unstructured settings.