IEEE J. Robotics Autom.最新文献_第8页

Minimizing turns for discrete movement in the interior of a polygon 多边形内部离散运动的最小转弯数

IEEE J. Robotics Autom. Pub Date : 1987-06-01 DOI: 10.1109/JRA.1987.1087092

J. Reif, J. Storer

引用次数: 29

The ground surveillance robot (GSR): An autonomous vehicle designed to transit unknown terrain 地面监视机器人(GSR):一种设计用于穿越未知地形的自动车辆

IEEE J. Robotics Autom. Pub Date : 1987-06-01 DOI: 10.1109/JRA.1987.1087091

S. Harmon

{"title":"The ground surveillance robot (GSR): An autonomous vehicle designed to transit unknown terrain","authors":"S. Harmon","doi":"10.1109/JRA.1987.1087091","DOIUrl":"https://doi.org/10.1109/JRA.1987.1087091","url":null,"abstract":"The Ground Surveillance Robot (GSR) project has proceeded continuously since the Fall of 1980, and in that time an autonomous vehicle design and some degree of implementation has been achieved. The vehicle design has been partitioned into sensor, control, and planning subsystems. A distributed blackboard scheme has been developed which provides the mechanism by which these subsystems are coordinated. Vehicle position and orientation are supplied by vehicle attitude and navigation sensor subsystems. Obstacle avoidance capability has been implemented by fusing information from vision and acoustic ranging sensors into local goals and avoidance points. The influence of these points is combined through potential field techniques to accomplish obstacle avoidance control. Distant terrain characteristics are identified using information from a gray-level vision system, a color vision system, and a computer-controlled laser ranging sensor. These characteristics are used by a general planning engine to develop the desired path to a visible goal in the direction of the final goal. Progress to the final goal consists of a succession of movements from one distant but visible intermediate goal to another. The experience from implementing this autonomous vehicle has indicated the need for an integrated set of debugging tools which make the faults in subsystem hardware and software more distinguishable.","PeriodicalId":370047,"journal":{"name":"IEEE J. Robotics Autom.","volume":"18 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114007492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 79

Sonar-based real-world mapping and navigation 基于声纳的真实世界地图和导航

IEEE J. Robotics Autom. Pub Date : 1987-06-01 DOI: 10.1109/JRA.1987.1087096

A. Elfes

{"title":"Sonar-based real-world mapping and navigation","authors":"A. Elfes","doi":"10.1109/JRA.1987.1087096","DOIUrl":"https://doi.org/10.1109/JRA.1987.1087096","url":null,"abstract":"A sonar-based mapping and navigation system developed for an autonomous mobile robot operating in unknown and unstructured environments is described. The system uses sonar range data to build a multileveled description of the robot's surroundings. Sonar readings are interpreted using probability profiles to determine empty and occupied areas. Range measurements from multiple points of view are integrated into a sensor-level sonar map, using a robust method that combines the sensor information in such a way as to cope with uncertainties and errors in the data. The resulting two-dimensional maps are used for path planning and navigation. From these sonar maps, multiple representations are developed for various kinds of problem-solving activities. Several dimensions of representation are defined: the abstraction axis, the geographical axis, and the resolution axis. The sonar mapping procedures have been implemented as part of an autonomous mobile robot navigation system called Dolphin. The major modules of this system are described and related to the various mapping representations used. Results from actual runs are presented, and further research is mentioned. The system is also situated within the wider context of developing an advanced software architecture for autonomous mobile robots.","PeriodicalId":370047,"journal":{"name":"IEEE J. Robotics Autom.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129294739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 696

Simulation of physical systems from geometric models 从几何模型模拟物理系统

IEEE J. Robotics Autom. Pub Date : 1987-06-01 DOI: 10.1109/JRA.1987.1087099

C. Hoffmann, J. Hopcroft

引用次数: 77

A survey and the future 一个调查和未来

IEEE J. Robotics Autom. Pub Date : 1987-04-01 DOI: 10.1109/JRA.1987.1087087

A. Bejczy, R. P. Paul

引用次数: 2

Sensor-based control of robotic manipulators using a general learning algorithm 基于传感器的机械臂控制的通用学习算法

IEEE J. Robotics Autom. Pub Date : 1987-04-01 DOI: 10.1109/JRA.1987.1087081

W. Miller

{"title":"Sensor-based control of robotic manipulators using a general learning algorithm","authors":"W. Miller","doi":"10.1109/JRA.1987.1087081","DOIUrl":"https://doi.org/10.1109/JRA.1987.1087081","url":null,"abstract":"A practical learning control system is described which is applicable to the control of complex robotic systems involving multiple feedback sensors and multiple command variables during both repetitive and nonrepetitive operations. In the controller, a general learning algorithm is used to learn to reproduce the relationship between the sensor outputs and the system command variables over particular regions of the system state space. The learned information is then used to predict the command signals required to produce desired changes in the sensor outputs. The learning controller requires no a priori knowledge of the relationships between the sensor outputs and the command variables, facilitating control system modification for specific applications. The results of two learning experiments using a General Electric P-5 manipulator are presented. The first involved learning to use the video image feedback to position the robot hand accurately relative to stationary objects on a table, assuming no knowledge of the robot kinematics or camera characteristics. The second involved learning to use video image feedback to intercept and track objects moving on a conveyor. In both experiments, control system performance was found to be limited by the resolution of the sensor feedback data, rather than by control structure limitations.","PeriodicalId":370047,"journal":{"name":"IEEE J. Robotics Autom.","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126553225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 334

A visual navigation system for autonomous land vehicles 一种用于自主陆地车辆的视觉导航系统

IEEE J. Robotics Autom. Pub Date : 1987-04-01 DOI: 10.1109/JRA.1987.1087089

A. Waxman, J. L. Moigne, L. Davis, B. Srinivasan, T. Kushner, Eli Liang, T. Siddalingaiah

{"title":"A visual navigation system for autonomous land vehicles","authors":"A. Waxman, J. L. Moigne, L. Davis, B. Srinivasan, T. Kushner, Eli Liang, T. Siddalingaiah","doi":"10.1109/JRA.1987.1087089","DOIUrl":"https://doi.org/10.1109/JRA.1987.1087089","url":null,"abstract":"A modular system architecture has been developed to support visual navigation by an autonomous land vehicle. The system consists of vision modules performing image processing, three-dimensional shape recovery, and geometric reasoning, as well as modules for planning, navigating, and piloting. The system runs in two distinct modes, bootstrap and feedforward. The bootstrap mode requires analysis of entire images to find and model the objects of interest in the scene (e.g., roads). In the feedforward mode (while the vehicle is moving), attention is focused on small parts of the visual field as determined by prior views of the scene, to continue to track and model the objects of interest. General navigational tasks are decomposed into three categories, all of which contribute to planning a vehicle path. They are called long-, intermediate-, and short-range navigation, reflecting the scale to which they apply. The system has been implemented as a set of concurrent communicating modules and used to drive a camera (carried by a robot arm) over a scale model road network on a terrain board. A large subset of the system has been reimplemented on a VICOM image processor and has driven the DARPA Autonomous Land Vehicle (ALV) at Martin Marietta's test site in Denver, CO.","PeriodicalId":370047,"journal":{"name":"IEEE J. Robotics Autom.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1987-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122281142","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 246

The effect of joint position errors of industrial robots on their performance in manufacturing operations 工业机器人关节位置误差对其制造作业性能的影响

IEEE J. Robotics Autom. Pub Date : 1987-04-01 DOI: 10.1109/JRA.1987.1087082

F. Azadivar

引用次数: 25

Introduction to robotics: Mechanics and control 机器人导论:力学与控制

IEEE J. Robotics Autom. Pub Date : 1987-04-01 DOI: 10.1109/JRA.1987.1087086

F. Merat

引用次数: 3465

Robot path planning using intersecting convex shapes: Analysis and simulation 使用相交凸形的机器人路径规划:分析与仿真

IEEE J. Robotics Autom. Pub Date : 1987-04-01 DOI: 10.1109/JRA.1987.1087080

Sanjiv Singh, M. D. Wagh

引用次数: 67