Local Planning of AUV Based on Fuzzy-Q Learning in Strong Sea Flow Field
ABSTRACT This article integrated reinforcement learning with fuzzy logic method for AUV local planning under the strong sea flow field. A fuzzy behavior is defined to resist the sea flow by giving a extra angle towards sea flow. And Q-learning is used to adjust the peak point of fuzzy membership function of the resisting sea flow behavior. This behavior is complemented by two other behaviors, the moving-to-goal behavior and collision avoiding behavior. The recommendations of these three behaviors are integrated through adjustable weighting factors to generate the final motion command for the AUV. Simulation shows it improve the adaptability of AUV under different sea flow greatly.
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ABSTRACT: An efficient, on-line terrain-covering algorithm is presented for a robot (AUV) moving in an unknown three-dimensional underwater environment. Such an algorithm is necessary for producing mosaicked images of the ocean floor. The basis of this three-dimensional motion planning algorithm is a new planar algorithm for nonsimply connected areas with boundaries of arbitrary shape. We show that this algorithm generalizes naturally to complex three-dimensional environments in which the terrain to be covered is projectively planar. This planar algorithm represents an improvement over previous algorithms because it results in a shorter path length for the robot and does not assume a polygonal environment. The path length of our algorithm is shown to be linear in the size of the area to be covered; the amount of memory required by the robot to implement the algorithm is linear in the size of the description of the boundary of the area. An example is provided that demonstrates the algorithm's per...Autonomous Robots 04/1999; · 1.91 Impact Factor
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ABSTRACT: Two types of computer boards incorporating recently developed VLSI fuzzy inferencing chips have been developed to support the addition of qualitative reasoning capabilities to the real-time control of robotic systems. The design and operation of these boards are first reviewed and their use, in conjunction with our proposed Fuzzy Behaviorist approach, is discussed. This approach uses superposition of elemental sensor-based behaviors expressed in the Fuzzy Sets theoretic framework, to emulate "human-like" reasoning inrobotic systems.Robotica 10/1994; 12(06):491 - 503. · 0.88 Impact Factor
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ABSTRACT: Most current architectures for autonomous robots are based on a decomposition of the control problem into small units of control, or behaviors. While this decomposition has a number of advantages, it brings about the problem of having to coordinate the execution of different units in order to obtain a globally coherent behavior. In this paper, we discuss how fuzzy logic can be used, and has been used, to address this problem. 1. Introduction Procs. of the 6th IEEE Int. Conf. on Fuzzy Systems (Barcelona, SP, july 1997) 573-578 The goal of autonomous robotics is to build physical systems that accomplish useful tasks without human intervention in real-world, unmodified environments --- that is, in environments that have not been specifically engineered for the robot. A major challenge of autonomous robotics is the large amounts of uncertainty that characterizes real-world environments. On the one hand, we cannot have exact and complete prior knowledge of these environments: many detail...09/1997;