Junjie Xie

Papers

Total Citations

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About

Junjie Xie is a robotics researcher focused on advancing human-robot interaction and adaptive control for assistive and service robots. His work primarily addresses the critical challenges of model uncertainty, vibration suppression, and autonomous decision-making in robotic systems. In his highly cited 2025 paper, Xie proposed an adaptive sliding mode control strategy based on radial basis function (RBF) neural networks for lower limb rehabilitation robots, effectively balancing compensation for model uncertainties with the need for smooth, stable motion. This contribution is pivotal for developing safer, more responsive rehabilitation devices. In related work from 2024, he developed a target grasping and multi-modal interaction system for the Pepper robot, integrating RGB-D vision, voice control, and adaptive grasping algorithms to move beyond rigid, preset programs toward more intelligent, flexible service robots. With over 1,000 citations to his key publications, Xie’s research is shaping the next generation of adaptive, human-aware robotic systems. His achievements include pioneering control strategies that directly enhance the safety and autonomy of robots in healthcare and domestic settings, marking him as a rising leader in intelligent robotics.