In factory automation, humans and robots comprise the two major work forces. Traditionally, humans and robots have not physically collaborated with each other during operation, in significant part because full automation with robots was the goal. In recent years, however, it has been recognized that there are tremendous advantages if robots are brought out of their cages and to allow them to share work space with and to collaborate with humans to take advantage of the best of two worlds – on one hand, the reliable execution of tasks by robots without wear handling objects of a wide range of sizes and weights, and on the other hand, the intelligence of humans and their five senses-based adaptability and flexibility. For collaboration between humans and robots to be successful, it is a prerequisite to ensure the safety of the humans in such collaboration. At the same time, it is important to ensure that robots collaborate with humans to ensure the best performance possible. The goal of this project is to establish a set of design principles of safe and efficient robot collaboration systems (SERoCS) for the next generation co-robots, which consists of robust cognition algorithms for environment monitoring, optimal task planning algorithms for safe human-robot collaboration, and safe motion planning and control algorithms for safe human-robot interactions (HRI). The proposed SERoCS will significantly expand the skill sets of the co-robots and prevent or minimize occurrences of human-robot collision and robot-robot collision during operation.
There are three main modules in the SERoCS system.
- Task 1. Environment Monitoring with Human Motion Prediction using camera captured signals
- Task 2. Task Planning with Skill Library that enables to co-robots to deal with difficult tasks
- Task 3. Safe and Efficient Motion Planning and Control in Real Time.
We also want to evaluate the overall performance of our system and provide some guidance for module and system design principles, therefore we have:
- Task 4. Evaluation of the SERoCS by Analyses, Simulations and Experiments
In task 2, we aim to expend the robot skill library. We teach the robot in many ways such as learning from human demostration and analogy learning. The goal is to teach the robot skills and allow the robot to generalize the skill to similer applications.
Subtopic 2.2. Task planning for intelligent co-robots | Brief |
- H.-C. Lin, C. Liu, and M. Tomizuka, “Fast robot motion planning with collision avoidance and temporal optimization,” in 2018 15th International Conference on Control, Automation, Robotics and
Vision (ICARCV), Singapore, 2018, pp. 29–35.
- C. Liu, T. Tang, H.-C. Lin, Y. Cheng, and M. Tomizuka, “SERoCS: Safe and efficient robot collaborative systems for next generation intelligent industrial co-robots,” arXiv:1809.08215, 2018.
- H.-C. Lin, T. Tang, Y. Fan, and M. Tomizuka, “A framework for robot grasp transferring with nonrigid transformation,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, 2018, pp. 2941–2948.
- Y. Cheng, W. Zhao, C. Liu, and M. Tomizuka, “Human motion prediction using semi-adaptable neural networks,” in 2019 American Control Conference (ACC). IEEE, 2019, pp. 4884–4890.
- J. Leu and M. Tomizuka, “Motion planning for industrial mobile robots with closed-loop stability enhanced prediction,” in ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers Digital Collection.
- J. Leu, R. Lim, and M. Tomizuka, “Safe and coordinated hierarchical receding horizon control for mobile manipulators,” in Proc. American Control Conference (ACC 2020), accepted, Jun. 2020.
- W. Zhao, L. Sun, C. Liu, and M. Tomizuka, “Experimental evaluation of human motion prediction: Toward safe and efficient human robot collaboration,” in Proc. American Control Conference (ACC 2020), accepted, Jun. 2020.
- Y. Cheng, L. Sun, and M. Tomizuka, “Towards efficient human robot collaboration with robust plan recognition and trajectory prediction,” in IEEE Robotics and Automation Letters, 2020.
Please send an email to Professor Masayoshi Tomizuka (firstname.lastname@example.org) and Jessica Leu (email@example.com) if you are interested in our Research Topics in Human-Robot Interaction and joining our group.
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