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Title of thesis: Control barrier function-enabled human-in-the-loop control for multi-robot systems

Time: Mon 2022-06-27 11.00 - 12.00

Location: Harry Nyquist MV10, floor 7

Video link: https://kth-se.zoom.us/j/63932462400?pwd=c3dyL3NFR3pWOVdycXd4T3VaUTk4UT09

Language: English

Respondent: Victor Nan Fernandez-Ayala , Reglerteknik/DCS

Opponent: Johanna Norén

Supervisor: Xiao Tan

Examiner: Dimos Dimarogonas

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Abstract: Autonomous multi-robot systems have found many real-world applications in factory settings, rescue tasks and light shows. Albeit these successful applications, the multi-robot system is usually pre-programmed with limited flexibility for online adaptation. Having a human-in-the-loop feature would provide additional flexibility such as handling unexpected situations, detecting and correcting bad behaviours and supporting the automated decision making. In addition, it would also allow for an extra level of cooperation between the robots and the human that facilitates certain real-world tasks, for example in the agricultural sector.

Control barrier functions (CBFs), as a convenient modular-design tool, will be mainly explored. CBFs have seen a lot of development in recent years and extending them to the field of multi-robot systems is still new. In particular, creating an original distributed approach, instead of a centralized one, will be one of the key topics of this Master’s thesis project.

In this thesis work, several multi-robot coordination protocols and safety constraints will be identified and these constraints will be enforced using a control barrier function-enabled mixer module. This module will take in the commands from both the planner and the human operator, prioritizing the commands from the human operator as long as the safety constraints are not violated. Otherwise, the mixer module will filter the commands and send out a safe alternative. The underlying multi-robot tasks are expected to be achieved whenever feasible. Simulations in ROS, Python and MATLAB environments are developed to experimentally assess the safety and optimality of the system, and experiments with real robots in a lab are performed to show the applicability of this algorithm.

Finally, a distributed approach to the mixer module has been developed, based on previous research and extended to allow for more versatility. This is of key importance since it would allow each robot to compute its own controller based on local information, making the multi-robot system both more robust and flexible to be deployed in real-world applications.