Collision Avoidance Control among Moving Obstacles for a Mobile Robot on the Fuzzy Reasoning
Yoichiro Maeda,Morikazu Takegaki +1 more
TLDR
Familiarity, adaptability, and adaptability are key characteristics of a truly democratic society.Abstract:
本論文ではファジィ推論およびプロダクションルールを適用した移動ロボットの障害物回避方式を提案する.本方式の第1ステップでは, ファジィ推論によりロボットと障害物との間の静的および動的危険度を認識する.第2ステップでは, この危険度を用いてディシジョンテーブルで回避方向を決定する.この方式を用いると動的障害物に対するヒューリスティック回避を実現できる.ここでは, 本方式の有効性を検証したシミュレーション結果について報告する.read more
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Book
Motion Planning in Dynamic Environments
TL;DR: This study of robot motion planning in dynamic domains presents algorithms for generating motion in an environment that changes over time and can serve as a reference for those working on spatial reasoning and autonomous robotic systems.
Journal ArticleDOI
On the design of an obstacle avoiding trajectory: Method and simulation
TL;DR: The paper suggests a new mathematical construction for the potential field used in the design of obstacle avoiding trajectories with the quickness of minimum computation and the compensation for the main drawbacks specific to the ''traditional approaches'' belonging to the possible field method in general.
Proceedings ArticleDOI
A method of indoor mobile robot navigation by using fuzzy control
TL;DR: A sensor-based navigation method using fuzzy control, whose purpose is to construct expert knowledge for efficient and better piloting of the AMRs, is presented and the effectiveness of the established rules and the effect of fuzzy control on AMR navigation are discussed on the basis of simulations.
Patent
Autonomous mobile machine, and system and method for controlling a mobile machine
TL;DR: In this paper, the authors used fuzzy inference to estimate the distance and angle from a predetermined path and the obstacle-free space ahead of the machine to avoid collisions with obstacles. But they did not consider the obstacle avoidance.
Proceedings ArticleDOI
On motion planning of mobile robots which coexist and cooperate with human
TL;DR: Simulation results revealed that robots can reach goals avoiding danger along appropriate trajectories and that this method is effective especially for the case where optimal trajectories dynamically vary according to change of human motion.