image: Lingfeng Tao
Credit: Raynard Churchwell / Kennesaw State University
Robots are becoming smarter and more common, but their ability to handle objects with human-like precision remains limited. At Kennesaw State University, new research is enabling robots to better understand movement, touch, and real-world interactions.
“My research focuses on dexterous manipulation,” said Lingfeng Tao, a Robotics and Mechatronics Engineering professor in Kennesaw State University’s Southern Polytechnic College of Engineering and Engineering Technology. “I want to control robot hands that are similar to the human hand, with multiple joints that can move independently and perform complex tasks.”
Tao is leading research that teaches robots how to manipulate objects with greater dexterity and awareness. His work focuses on enabling robotic hands to move more naturally during remote and autonomous operations. The research is supported by a $300,000 National Science Foundation (NSF) grant, as well as a $40,000 NVIDIA Academic Grant that provides advanced AI hardware.
Unlike simple robotic grippers that can only open and close, Tao’s research centers on multi-finger robotic hands capable of rotating objects, using tools, and adjusting grip based on physical interaction. These abilities require advanced artificial intelligence (AI) to replicate what humans do instinctively.
Traditional remotely controlled robotic systems often rely on tracking human hand movements and mapping those motions directly to a robot. Tao said this approach ignores physical interaction, forcing human operators to move slowly and carefully to compensate for the robot’s lack of awareness.
“When humans manipulate objects, there are physical interactions happening,” Tao said. “If you only map human motion to the robot, the robot cannot understand or feel those interactions.”
To address this, Tao uses deep reinforcement learning to train robots in simulated environments where thousands of virtual robots practice tasks simultaneously. The AI learns from both success and failure before being applied to physical systems.
“We collect all of those experiences,” Tao said. “The AI learns how to avoid failure and encourage successful behavior.”
Tao often compares robotic learning to how children learn to use tools.
“A kid already has basic abilities from playing with toys,” he said. “They watch adults, learn how the tool is used, and then apply their own skills.”
This approach allows robots to follow high-level human intent while handling low-level manipulation tasks independently, enabling long-distance control in environments that are dangerous or inaccessible to people. Tao said this balance between autonomy and human guidance is key to improving both performance and safety.
“You could send a robot to the moon or to deep-sea environments,” Tao said. “The human can still control it to do very subtle, dexterous tasks.”
Applications of the research include robotic surgery, space exploration, disaster response, manufacturing, and healthcare.
SPCEET Dean Lawrence Whitman said Tao’s work reflects the college’s innovation in research that shapes our future.
“Dr. Tao’s research unites artificial intelligence and robotics to change the way we live and work,” Whitman said. “His work is a shining example of research designed to understand problems and seek innovative solutions to a range of grand societal challenges.”
Tao joined Kennesaw State in August and is establishing research labs on the Marietta Campus, including a robotics lab in the Crawford Building. His research team includes graduate students who contribute to system development, simulation testing, and real-world validation.
Looking ahead, Tao aims to integrate robotic control and feedback into a single system capable of handling long, multi-step tasks.
“If robots are going to enter everyday life, safety and reliability are critical,” Tao said. “Our goal is to make robots intelligent, safe, and truly helpful to people.”