A Collaborative Path Planning for Multiple Mobile Robots Based on TANGENT and Contract Net Protocol

In recent years, with the rapid development of robotics, a large number of robots are used in various fields such as industry, military, agriculture, and aerospace. Robots are gradually expected to take on more kinds of tasks. The cooperative multiple robot team is much more adapt than single robot to executing sophisticated and unstructured mission due to its advantages in robustness, adaptability and distribution both in time and space. To improve the overall mission performance of the cooperation between multiple robots controlled in a distributed mode is one of the most interesting and prospecting research directions in robotics. This is not only a simple linear addition of the processing capacity of a single robot, but also an increment generated by robot interaction and information sharing. Currently the research of distributed multi-robot control is mostly focused on the construction of global maps, border lookout, clean ground etc. The common point of these tasks is that the subtasks of each robot are similar to the global task except for the scale. The coupling between these subtasks is loose. However, when dealing with other complex tasks, the robot team is expected to cooperate more intelligently. This paper will try to construct a collaborative path planning framework for multiple mobile robotic systems in unknown environments. The difficulty of this framework is that distributed control system for multiple mobile robots has no central control node, while at the same time requiring the maintenance of a common mind such as path planning among robot team members. The contract net protocol and algorithm of TANGENT are applied to solve two fundamental issues for the collaborative path planning of multiple robots, of which one is the collaboration protocol and the other one is the environment modeling and navigation. Then the path planning is combined with the mission cooperation of multiple robots through a dynamic updating policy of mission sequence, in which a series of tasks is generated and released simultaneously to all the members of the team to guide the team to collectively behave in the environment as if a single robot behaves in local path planning. Thus, the problem is reduced to dynamically instruct the team members to complete these known tasks based on the sequence. In such a dynamic collaboration framework, the task sequence is dynamically changing and the generation of new task sequence will depend on how the tasks are performed, which means the environment modeling, navigation, task generation and team execution are continuously influencing each other in the whole process. This gives robot team cooperating based on this framework the ability to cope with dynamically changing environments, increase or decrease in number of members. Multiple KUKA Youbot robots will be used to build a simulation environment in Robot Operating System to implement the above framework and perform simulation experiments. At the same time, the map information transferred between robots is compressed in the experiment. The robustness, fluency, rapidity, power consumption, communication burden and other performances of this multi-robot system are analyzed and compared.