A Multi-agent Simulation Model Based on Fuzzy Logic to Predict Conflict Situations for Autonomous Robot Navigation

One of the current challenges in the development of robot control systems is making them capable of intelligent and suitable responses to changing environments. But, the control of the robot´s behavior in uncertain and dynamic environments is very challenging when the problem is how to guarantee the robot´s safety by minimizing the interaction with other actors. The most popular methods are based on reactive local navigation schemes that tightly couple the robot actions to the sensor information. These approaches are well based on distance between the robot and the obstacles. This information does not allow the robot to make an intelligent decision while it navigates in unknown environments. Whereas, the robot needs to anticipate environment evolution in order to minimize interaction and avoid conflict with other agents. In this paper, we present a multi-agent simulation model of an autonomous robot in dynamic and uncertain environments. We focus on cases of interactions between agents sharing the same space. The robot should minimize the conflict with other agents when it navigates headed for its goal. Our model is based on fuzzy logic technique in order to deal with the uncertainty of perception.