Abstract
A new behavior-based fuzzy control method for mobile robot navigation is presented. It is based on behavioral architecture which can deal with uncertainties in unknown environments and has the ability to accommodate different behaviors. Basic behaviors are controlled by specific fuzzy logic controllers, respectively. The proposed approach qualifies for driving a robot to reach a target while avoiding obstacles in the environment. Simulation and experiments are performed to verify the correctness and feasibility of the proposed method.
Highlights
One way to accomplish robot navigation is using behavior arbitration and behavior control [1, 2]
We decompose the task of robot navigation into three elementary behaviors: goal seeking (GS), obstacle avoidance (OA), and behavior fusion (BF)
The robot is set at the start point = (0, 0) and the goal is defined in Cartesian coordinates with the position of = (3, 5)
Summary
One way to accomplish robot navigation is using behavior arbitration and behavior control [1, 2]. Since the behavior control architecture was proposed in 1986, it has been adopted to solve the robot navigation problem frequently. In [13], Wang et al proposed behavior-based hierarchical fuzzy control method for mobile robot navigation in dynamic environment. Fuzzy logic controllers can be used for driving mobile robot to perform specific motions with good robustness. A way of solving this problem is to create a fundamental or basic controller which can be incrementally updated and optimized by tuning both labels and rules adequately Another way of solving this problem is to decompose the complex behavior into several subbehaviors or motions which are controlled by separate schema. This paper will address the mobile robot navigation issue by combining the ideas of behavior-based control and fuzzy logic control.
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