Abstract
Navigation of a wheeled robot in unknown environments is proposed in this paper. The approach may be applied to navigating an autonomous vehicle in unknown environments, such as parking lots. The navigation consists of three parts: obstacle avoidance behavior, target seeking behavior, and a behavior supervisor. The obstacle avoidance behavior is achieved by controlling the robot to move along an obstacle boundary through evolutionary fuzzy control. In the evolutionary fuzzy control approach, a Pareto set of fuzzy controllers (FCs) is found though a multi-objective continuous ant colony optimization algorithm. Target seeking behavior is achieved by controlling the robot through hybrid proportional–integral–derivative (PID) controllers. The behavior supervisor determines the switching between obstacle avoidance and target seeking behaviors, where the dead-cycle problem is considered. Simulations and experiments were performed to verify the effectiveness of the proposed navigation scheme.
Highlights
Navigation is an important task for autonomous vehicles and robots
Results and Discussion sensing range and no obstacle is found in the target regions, the robot switches from obstacle boundary following (OBF) to target searching (TS)
The results showed that the fuzzy controllers (FCs)-C controlled robot moved a shorter distance distance than the FC-S and fuzzy controllers with the best position performance (FC-P) controlled robots
Summary
Navigation is an important task for autonomous vehicles and robots. Localization is an important function in navigation. The sensors generally used in the positioning system of autonomous vehicles include Global Positioning Systems (GPS), inertial measurement units, Light Detection and Ranging (LIDAR), and camera sensors [1,2]. When lane markings are available, lane-detection systems, based on LIDAR [3], and/or cameras [4,5], can provide lateral distance measurements from the lane markings to the vehicle for lane-level navigation [6]. In unknown environments without lane markings, such as basements and suburbs, another navigation approach needs to be developed. The techniques of robot navigation in unknown environments may be employed to address this problem
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