Dependable Path Planning for Autonomous Control

Changing from automatic to autonomous control has emerged as the main shift on the development of robots nowadays. The autonomous control allows robot to have more freedom as well as direct interactions with human and other robots. Having a dependable platform for autonomous control becomes crucial when building such a system. The dependability of a robotic agent is presented by main attributes including availability, i.e. the continuous operations of the system over a time interval, reliability, i.e. the ability of the system to provide correct services, and safety, i.e. the robotic agent must ensure safe controls to avoid any catastrophic consequences on users, other robots, and finally the environment. Considering path planning is one of the key components of an autonomous control system for robotic agents, the works presented in this thesis aim at building a dependable, i.e. safe, reliable and effective, path planning algorithm for a group of robots that share their working space with humans. Firstly, the method for path planning of multiple robotic agents is proposed based on a novel dipole flow field idea.The any angle-path planning with Theta* algorithm is employed to initialise the paths from a starting point to a goal for a set of agents. To deal with static obstacles while a robot is going on the way to its goal, a static flow field along the configured path is defined. A dipole field is then calculated to avoid the collision of agents with the other agents and human subjects. In this approach, each robotic agent is assumed to be a source of a magnetic dipole field in which the magnetic moment is aligned with the moving direction of the agent, with a strength proportional the velocity. The magnetic dipole-dipole interactions between these agents generate repulsive forces to help them to avoid collision. Meanwhile, the fault analysis of multiple robots with Petri net is demonstrated to understand the cooperation of multiple robotic agents to solve the shared tasks. Thereafter, the Petri net is applied together with the path planning to address the collision avoidance by synchronising the movement of robots through a cross. Continuously, the multiple path planning has investigated to support fault tolerance for the path planning algorithm. This is to deal with the deadlock situation where the agent takes very long time to reach the goal or even is not able to do so. The agent is equipped with different paths to the goal and proactively switch among the plans whenever needed to avoid the deadlock. Finally, the whole framework has been implemented by a widely used platform, robot operating system (ROS), and evaluated through Gazebo simulator