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About

Jianxin Chen is a robotics researcher whose work focuses on human-robot interaction, motion imitation, and autonomous perception. His key research areas include humanoid robot control, inverse kinematics, and real-time distance estimation for robotic systems. Chen’s most cited paper, "Lower-body control of humanoid robot NAO via Kinect" (2017, 15 citations), demonstrates his early contributions to intuitive robot control using consumer-grade sensors. His 2018 paper on "Work chain-based inverse kinematics of robot to imitate human motion with Kinect" (11 citations) addresses the fundamental challenge of bridging physical differences between humans and robots to enable natural motion imitation—a critical step toward more intelligent, responsive AI systems. Chen also contributed to practical robot applications, including a stereo-camera-based moving object distance estimation method (2019, 8 citations) that balances accuracy and computational efficiency for navigation and obstacle avoidance. His work extends to mobile app testing via robots (2020) and tactile-feedback human-computer interaction (2021), showcasing his versatility. With a total of over 40 citations across his published works, Chen has established himself as a researcher dedicated to making robots more perceptive, interactive, and capable of mimicking human actions in real-world settings.