Multi-robot coordination and planning with human-in-the-loop under STL specifications : Centralized and distributed frameworks

Sammanfattning: Recent urbanization and industrialization have brought tremendous pressure and challenges to modern autonomous systems. When considering multiple complex tasks, cooperation and coordination between multiple agents can improve efficiency in a system. In real-world applications, multi-agent systems (MAS) are widely used in various fields, such as robotics, unmanned aerial systems, autonomous vehicles, distributed sensor networks, etc. Unlike traditional MAS systems based on pre-defined algorithms and rules, a special human-in-loop (HIL) based MAS involves human interactions to enhance the system’s adaptability for special scenarios, as well as apply human preferences for robot control. However, existing HIL strategies are primarily based on human involvement at a low level, such as mixed-initiative control and mixed-agent scenarios with both human-driven and intelligent robots. There are fewer investigations on applying HIL in high-level coordination. In particular, designing a coordination strategy for multi-task multi-agent scenarios, which can also deal with real-time human commands, will be one of the key topics of this Master’s thesis project. In this thesis work, different kinds of tasks described by signal temporal logic (STL) are created for agents, which can be enforced by control barrier function (CBF) constraints. Both centralized and distributed frameworks are designed for agent coordination. In detail, the centralized strategy is developed for machine-to-infrastructure (M2I) communication, by using the nonlinear model predictive control (NMPC) method to obtain collision-free trajectories. The distributed strategy utilizing graph theory is proposed for machine-to-machine (M2M), in order to reduce computation time by offloading. Most importantly, a HIL model is generated for both frameworks to apply online human commands to the coordination, with a novel task allocation protocol. Simulations and experiments are carried out on both Matlab and Python-based ROS simulators, to show that proposed frameworks can achieve obvious performance advantages in safety, smoothness, and stability for task completion. Numerical results are provided to validate the feasibility and applicability of our algorithms.