Task Allocation And Collision Avoidance Policy For Multiple UGV Systems Using Colored Petri Nets

Unmanned ground vehicles(UGVs) are the vehicles that operate in contact with the ground and without an onboard human presence. Generally, the vehicles will have a set of sensors to observe the environment, and will either autonomously make decisions about its behavior or pass the information to a human operator at a different location who will control the vehicle through teleoperation. UGVs can be widely used for many applications including industrial automation, disaster rescue, intelligent traffic, and military operation. Along with the development of robot technology, the intelligence and performance of a UGV has been significantly improved. However, with the increasing complexity and diversity of missions, a single UGV's performance is no longer able to satisfy the task requirements. It is necessary to develop ways for multiple UGVs to work together as a collaborative group.In terms of the group control of UGV systems, the goal is to plan an optimal route for each UGV such that they can accomplish all the tasks without collisions. It means that the problem of task allocation and collision avoidance are the two key issues for serving all the tasks.This thesis is motivated to deal with the multiple UGVs system by focusing on the problem of task allocation and collision avoidance. Colored Petri nets(CPNs) are used to model and analyze the dynamics of the UGVs systems. CPNs are widely used to model discrete event systems thanks to their compactness to describe complex networked systems. Compared to general Petri nets(PNs), they allow many folding techniques so as to condense the system model. With them, many control synthesis problems are reduced to the solution of matrix operations. Supervisory control techniques can be realized in a computationally efficient way.The main contributions of this thesis are described as follows:(1) This thesis simplifies the model of working environment for a multiple UGVs system and proposes a CPN model that embeds the environment locations and the possible UGV movements.(2) Based on the study of the former research on task allocation for multiple UGVs using PN, this thesis extends the method to CPN, overcomes the former's problem that different kinds of UGVs cannot be distinguished during the control process.(3) This thesis presents the control policy for the avoidance of the possible collisions between UGVs. In this policy, the working space of UGVs is divided into smaller regions so that the collision avoidance problem is equivalent to the capacity constraint of each part. CPNs are used to model the dynamics of the UGVs system and the collision avoidance policy is expressed by colored GMECs.