This article proposes a betterment process for the operation of a mechanical robot in a sense that it betters the next operation of a robot by using the previous operation's data. The process has an iterative learning structure such that the (k + 1)th input to joint actuators consists of the kth input plus an error increment composed of the derivative difference between the kth motion trajectory and the given desired motion trajectory. The convergence of the process to the desired motion trajectory is assured under some reasonable conditions. Numerical results by computer simulation are presented to show the effectiveness of the proposed learning scheme.

Bettering Operation of Robots by Learning

A methodology for exact robot motion planning and control that unifies the purely kinematic path planning problem with the lower level feedback controller design is presented. Complete information about a freespace and goal is encoded in the form of a special artificial potential function, called a navigation function, that connects the kinematic planning problem with the dynamic execution problem in a provably correct fashion. The navigation function automatically gives rise to a bounded-torque feedback controller for the robot's actuators that guarantees collision-free motion and convergence to the destination from almost all initial free configurations. A formula for navigation functions that guide a point-mass robot in a generalized sphere world is developed. The simplest member of this family is a space obtained by puncturing a disk by an arbitrary number of smaller disjoint disks representing obstacles. The other spaces are obtained from this model by a suitable coordinate transformation. Simulation results for planar scenarios are provided. >

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Exact robot navigation using artificial potential functions

Motion planning is one of the most important areas of robotics research. The complexity of the motion-planning problem has hindered the development of practical algorithms. This paper surveys the work on gross-motion planning, including motion planners for point robots, rigid robots, and manipulators in stationary, time-varying, constrained, and movable-object environments. The general issues in motion planning are explained. Recent approaches and their performances are briefly described, and possible future research directions are discussed.

Gross motion planning—a survey

A path-planning algorithm for the classical mover's problem in three dimensions using a potential field representation of obstacles is presented. A potential function similar to the electrostatic potential is assigned to each obstacle, and the topological structure of the free space is derived in the form of minimum potential valleys. Path planning is done at two levels. First, a global planner selects a robot's path from the minimum potential valleys and its orientations along the path that minimize a heuristic estimate of the path length and the chance of collision. Then, a local planner modifies the path and orientations to derive the final collision-free path and orientations. If the local planner fails, a new path and orientations are selected by the global planner and subsequently examined by the local planner. This process is continued until a solution is found or there are no paths left to be examined. The algorithm solves a much wider class of problems than other heuristic algorithms and at the same time runs much faster than exact algorithms (typically 5 to 30 min on a Sun 3/260). >

A potential field approach to path planning

This study of robot motion planning in dynamic domains presents algorithms for generating motion in an environment that changes over time. Their computational costs are also analyzed. The ability to plan motion in a dynamic domain is of critical importance to an autonomous robotic system that must operate in the presence of moving obstacles or other robots. The most important feature of the book is the presentation of algorithmic solutions to geometric aspects of dynamic motion planning problems which are of fundamental importance in robotics. Topics discussed include planning in time-dependent environments, generation of time-minimal paths in three dimensions, and the co-ordination of multiple mobile agents. The book can serve as a reference for those working on spatial reasoning and autonomous robotic systems.

Motion Planning in Dynamic Environments

The authors have been studying a mobile robot for inspection of the high voltage power transmission lines stretched between towers. The robot can run on a ground wire stretched on the top of the towers and go over the towers. In this paper, we propose a unique locomotive mechanism for the robot equipped with four crawlers, two arms with pulleys, and four actuators. It can go over the towers with stable state, and does not damage the towers and equipments on them. Geometrical conditions for the design of the mechanism and its details are described. A half scale model of the mechanism is constructed. It is confirmed by experiments that the mechanism can successfully go over the tower automatically with keeping static stability.

Development of a Mobile Inspection Robot for Power Transmission Lines

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.

Collision Avoidance Control among Moving Obstacles for a Mobile Robot on the Fuzzy Reasoning

Sensory Feedback Based on the Artificial Potential for Robot Manipulators

PURPOSE: To obtain an automatic travelling machine which can pass obstacles without trouble and can travel over a long distance, by arranging the plural sets of travelling rollers for inserting a stringing into a space between both sides with inserting mechanisms, and a bearing pulley rolling slantly on the stringing. CONSTITUTION: In the front and rear of a frame unit 21 containing a driving source 22 and a controller 23, a plurality of every set of bearing arms 24 on both sides are arranged movably in the side directions. The bearing arms 24 clip from both sides with clipping mechanisms (stretching springs) 28. Besides, on the respective bearing arms 24, travelling rollers 25 are fitted to be suspended, and are contrived to be travelled inserting a stringing 3 into a space between the rollers 25 with rotational driving sources 27. Then, at the intermediate section of the frame unit 21, a bearing pulley 29 is set. The bearing pulley 29 is contrived to be butted onto the stringing 3 alternately and slantly from the left and right, and is supported to be moved in the vertical direction. COPYRIGHT: (C)1989,JPO&Japio

Automatic travelling machine

We report a method for obstacle avoidance control against moving or standing obstacles for mobile robot. The speed of moving obstacles is uncertain, and their speed is expressed using fuzzy numbers. This paper presents an obstacle avoidance algorithm using fuzzy production system. Some results of computer simulation are shown to evaluate the effectiveness of the proposed method.

Yoichiro Maeda

Papers

Development of a Mobile Inspection Robot for Power Transmission Lines

Collision Avoidance Control among Moving Obstacles for a Mobile Robot on the Fuzzy Reasoning

Sensory Feedback Based on the Artificial Potential for Robot Manipulators

Automatic travelling machine

Study of Obstacle Avoidance Problem for Mobile Robot Using Fuzzy Production System