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About

Kesheng Wang is a researcher whose work spans robotics, intelligent manufacturing, and advanced sensing technologies, with particular expertise in evolutionary computation applied to robotic systems. His most significant contributions lie in the application of genetic algorithms to robot kinematics calibration, where he addressed the practical challenge of achieving end-effector precision by optimizing physical parameter values — work that has garnered 22 citations and remains a key reference in robot calibration methodology. Wang has also made notable contributions to mobile robot path planning, developing the Step-Spreading Map algorithm to guide multi-objective genetic algorithm optimization, earning 11 citations, as well as domain-specific planning solutions for greenhouse robotics environments. His earlier work in holonic manufacturing systems and computer graphics simulation for robot manipulators demonstrates a career-long engagement with intelligent, adaptive robotic architectures dating back to 1989. More recently, Wang has expanded into flexible electronics and tactile sensing, proposing a self-powered, transparent sensor capable of integrating sliding and proximity detection — signaling a forward-looking pivot toward intelligent perception for next-generation robotics. His body of work reflects a sustained commitment to bridging computational intelligence with practical robotic and manufacturing applications.