Bo Su

Robotics Engineer specializing in human-robot collaboration and tactile sensing

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Email: bobobobosu@gmail.com

Phone: +1 (408) 529-8081

I am a Robotics Engineer specialized in developing algorithms that enable robots to learn from human demonstration. As a recent Carnegie Mellon University graduate with an M.S. in Electrical & Computer Engineering, my research focuses on human-robot collaboration, tactile sensing, and multi-robot coordination.

My expertise lies in motion planning and trajectory optimization, with a strong background in implementing perception-planning-control stacks for industrial automation. I’ve developed systems that can achieve precise manufacturing tasks while adapting to environmental variations and human feedback.

Research Interests

  • Human-Robot Collaboration: Creating systems where robots learn from physical human feedback
  • Tactile Sensing: Developing electronic textile skins for safer robot control
  • Multi-Robot Coordination: Optimizing workcell layouts and trajectories for industrial applications
  • Motion Planning: Implementing kinodynamic motion planners for manipulators

Education

  • M.S. in Electrical & Computer Engineering, Carnegie Mellon University (2022-2024)
  • B.S. in Computer Science, University of California, San Diego (2019-2021)

I’m passionate about creating interactive robots that respond intelligently to human guidance and environmental constraints. Feel free to explore my publications and projects, or reach out to discuss potential collaborations.

selected publications

  1. ICRA
    Optimizing Multi-Touch Textile and Tactile Skin Sensing Through Circuit Parameter Estimation
    B. Y. Su, Y. Wu, C. Wen, and 1 more author
    In 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024
  2. ASME
    Customizing Textile and Tactile Skins for Interactive Industrial Robots
    B. Y. Su, Z. Wei, J. McCann, and 2 more authors
    ASME Letters in Dynamic Systems and Control, 2023
  3. ICRA
    Learning from physical human feedback: An object-centric one-shot adaptation method
    A. Shek, B. Y. Su, R. Chen, and 1 more author
    In 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023
    Best Physical Human Interaction Paper Award