A Distributed Vision Infrastructure for Multi-Robot Localization

2007 ◽  
Author(s):  
Brian Stancil ◽  
Hsiang-Wen Hsieh ◽  
Tsuhan Chen ◽  
Hung-Hsiu Yu
Keyword(s):  
Coordinate System ◽  
Vision System ◽  
Reference Plane ◽  
Robot Localization ◽  
Multiple Robots ◽  
Base Process ◽  
World Coordinate System ◽  
Distributed Vision ◽  
Coordinate Transform ◽  
Multi Robot

Localization is one of the critical issues in the field of multi-robot navigation. With an accurate estimate of the robot pose, robots will be able to navigate in their environment autonomously with the aid of flexible path planning. In this paper, the infrastructure of a Distributed Vision System (DVS) for multi-robot localization is presented. The main difference between traditional DVSs and the proposed one is that multiple overhead cameras can simultaneously localize a network of robots. The proposed infrastructure is comprised of a Base Process and Coordinate Transform Process. The Base Process receives images from various cameras mounted in the environment and then utilizes this information to localize multiple robots. Coordinate Transform Process is designed to transform from Image Reference Plane to world coordinate system. ID tags are used to locate each robot within the overhead image and camera intrinsic and extrinsic parameters are used to estimate a global pose for each robot. The presented infrastructure was recently implemented by a network of small robot platforms with several overhead cameras mounted in the environment. The results show that the proposed infrastructure could simultaneously localize multiple robots in a global world coordinate system with localization errors within 0.1 meters.

Use of the FITS World Coordinate System by STEREO/SECCHI

Solar Physics ◽  
2009 ◽  
Vol 261 (1) ◽  
pp. 215-222 ◽  
Author(s):  
W. T. Thompson ◽  
K. Wei
Keyword(s):  
Coordinate System ◽  
World Coordinate System

A Self-Calibration Method for Robotic Measurement System

1999 ◽  
Author(s):  
Chunhe Gong ◽  
Jingxia Yuan ◽  
Jun Ni
Keyword(s):  
Coordinate System ◽  
Measurement System ◽  
Calibration Method ◽  
Position Measurement ◽  
Robot Calibration ◽  
Robot System ◽  
Self Calibration ◽  
World Coordinate System ◽  
Robot Accuracy ◽  
Calibration Methods

Abstract Robot calibration plays an increasingly important role in manufacturing. For robot calibration on the manufacturing floor, it is desirable that the calibration technique be easy and convenient to implement. This paper presents a new self-calibration method to calibrate and compensate for robot system kinematic errors. Compared with the traditional calibration methods, this calibration method has several unique features. First, it is not necessary to apply an external measurement system to measure the robot end-effector position for the purpose of kinematic identification since the robot measurement system has a sensor as its integral part. Second, this self-calibration is based on distance measurement rather than absolute position measurement for kinematic identification; therefore the calibration of the transformation from the world coordinate system to the robot base coordinate system, known as base calibration, is not necessary. These features not only greatly facilitate the robot system calibration but also shorten the error propagation chain, therefore, increase the accuracy of parameter estimation. An integrated calibration system is designed to validate the effectiveness of this calibration method. Experimental results show that after calibration there is a significant improvement of robot accuracy over a typical robot workspace.

Development of a distributed vision system for industrial conditions

2003 ◽  
Author(s):  
Michael Weiss ◽  
Arnulf Schiller ◽  
Paul O'Leary ◽  
Ewald Fauster ◽  
Peter Schalk
Keyword(s):  
Vision System ◽  
Distributed Vision System ◽  
Distributed Vision

scholarly journals Multi-Robot Coverage and Persistent Monitoring in Sensing-Constrained Environments

Robotics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 47
Author(s):  
Tauhidul Alam ◽  
Leonardo Bobadilla
Keyword(s):  
Regions Of Interest ◽  
Multiple Robots ◽  
Periodic Trajectories ◽  
Practical Utility ◽  
Physical Experiments ◽  
Constrained Environments ◽  
Limited Sensing ◽  
Contact Sensors ◽  
Multi Robot ◽  
Persistent Monitoring

This article examines the problems of multi-robot coverage and persistent monitoring of regions of interest with limited sensing robots. A group of robots, each equipped with only contact sensors and a clock, execute a simple trajectory by repeatedly moving straight and then bouncing at perimeter boundaries by rotating in place. We introduce an approach by finding a joint trajectory for multiple robots to cover a given environment and generating cycles for the robots to persistently monitor the target regions in the environment. From a given initial configuration, our approach iteratively finds the joint trajectory of all the robots that covers the entire environment. Our approach also computes periodic trajectories of all the robots for monitoring of some regions, where trajectories overlap but do not involve robot-robot collisions. We present experimental results from multiple simulations and physical experiments demonstrating the practical utility of our approach.

A Multi-Robot System Using Mobile Agents with Ant Colony Clustering

2010 ◽  
pp. 174-192
Author(s):  
Yasushi Kambayashi ◽  
Yasuhiro Tsujimura ◽  
Hidemi Yamachi ◽  
Munehiro Takimoto
Keyword(s):  
Communication Networks ◽  
Mobile Agents ◽  
Software Agents ◽  
Ant Colony ◽  
Multiple Robots ◽  
Robot System ◽  
Mobile Software ◽  
Robot Systems ◽  
Ant Colony Clustering ◽  
Multi Robot

This chapter presents a framework using novel methods for controlling mobile multiple robots directed by mobile agents on a communication networks. Instead of physical movement of multiple robots, mobile software agents migrate from one robot to another so that the robots more efficiently complete their task. In some applications, it is desirable that multiple robots draw themselves together automatically. In order to avoid excessive energy consumption, we employ mobile software agents to locate robots scattered in a field, and cause them to autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO) method. ACO is the swarm-intelligence-based method that exploits artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. Even though there is much room to improve the collaboration of multiple agents and ACO, the current results suggest a promising direction for the design of control mechanisms for multi-robot systems. In this chapter, we focus on the implementation of the controlling mechanism of the multi-robot system using mobile agents.

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