Research Mentor
Research Mentor
Lingfeng Tao, Ph.D., Assistant Professor
Office: 563 Engineering North
Phone: 405-744-5140
Email: lingfeng.tao@okstate.edu
Research problem and objectives
Research problem and objectives
The integration of AI and machine learning has significantly advanced the capabilities of physical robots, particularly in their potential role within Smart Personal Protective Equipment (SmaPP). This project, led by Dr. Tao, focuses on a critical aspect of this integration: ensuring safe physical interactions between humans and robots in complex, real-world settings while the robots perform protective functions (Figure 1). The investigation will cover a range of challenges in SmaPP, spanning from high-level human-robot interaction strategies to the more technical aspects of safe robot execution and control methods. This comprehensive study aims to address both foundational and progressive hurdles in the field, maintaining a balance between advanced robot intelligence and safety in human-robot collaborations.
Student Project and Research Activities
Student Project and Research Activities
AI Technology for Robot Control: The student will learn key AI technology for robot control based on Deep Reinforcement Learning algorithms. Instructions and coding examples will be provided. Students will be provided with high-performing computers to practice AI training in the simulated environment.
Human Intent Modelling and Perception: The student will study how to understand and model human intent through sensory data and study what forms of human perception, including visual, acoustic, thermal, and haptics, can help to increase the ubiquitous acceptance of SmaPP.
Safe Human-Robot Interaction Strategies Development: Students will utilize the AI technology, human intent model, and optimized human perception to design safe human-robot interaction strategies that can increase the user's comfort, satisfaction, and subjective feeling. The strategies will be tested on the physical robot hand in real-world experiments. The student will conduct an experiment design and develop evaluation metrics to measure the performance of the developed teleoperation system.
Student Qualifications and Skills
Student Qualifications and Skills
Undergraduate standing (at least left with one semester for graduation)
Experience in robotics modeling, simulation and control
Electrical Engineering/computer engineering/Computer Science/Mechanical Engineering/Mechatronics and Robotics majors
Python/C++/Matlab programming skills
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