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.

scholarly journals Cost-efficient inter-robot delivery for resource-constrained and interdependent multi-robot schedules

2019 ◽  
Vol 16 (1) ◽  
pp. 172988141982804 ◽  
Author(s):  
Yin Chen ◽  
Xinjun Mao ◽  
Shuo Yang ◽  
Qiuzhen Wang
Keyword(s):  
Cost Efficiency ◽  
Resource Constrained ◽  
Task Execution ◽  
Robot System ◽  
Sequential Execution ◽  
Constrained Environments ◽  
Cost Efficient ◽  
The Cost ◽  
Multi Robot

A multi-robot system in resource-constrained environments needs to obtain resources for task execution. Typically, resources can be fetched from fixed stations, which, however, can be costly and even impossible when fixed stations are unavailable, depleted or distant from task execution locations. We present a method that allows robots to acquire urgently required resources from those robots with superfluous residual resources, by conducting rendezvouses with these robots. We consider a scenario where tasks are organised into a schedule on each robot for sequential execution, with cross-schedule dependencies for inter-robot collaboration. We design an algorithm to systematically generate such rendezvouses for entire multi-robot system to increase the proportion of tasks whose resource demands are satisfied. We also design an algorithm that periodically reallocates tasks among robots to improve the cost-efficiency of schedules. Our experiment shows the synergetic effectiveness of both algorithms, when fixed stations are unavailable and all resources are fetched through inter-robot delivery. We also investigate the effectiveness of inter-robot delivery in scenarios where fixed stations are existent but distant from the locations of tasks.

scholarly journals A Review on Map-Merging Methods for Typical Map Types in Multiple-Ground-Robot SLAM Solutions

Sensors ◽  
2020 ◽  
Vol 20 (23) ◽  
pp. 6988
Author(s):  
Shuien Yu ◽  
Chunyun Fu ◽  
Amirali K. Gostar ◽  
Minghui Hu
Keyword(s):  
Multiple Robots ◽  
Working Mechanism ◽  
Topological Maps ◽  
Occupancy Grid ◽  
Localization And Mapping ◽  
Robot Systems ◽  
Feature Based ◽  
Occupancy Grid Maps ◽  
Multi Robot ◽  
Map Merging

When multiple robots are involved in the process of simultaneous localization and mapping (SLAM), a global map should be constructed by merging the local maps built by individual robots, so as to provide a better representation of the environment. Hence, the map-merging methods play a crucial rule in multi-robot systems and determine the performance of multi-robot SLAM. This paper looks into the key problem of map merging for multiple-ground-robot SLAM and reviews the typical map-merging methods for several important types of maps in SLAM applications: occupancy grid maps, feature-based maps, and topological maps. These map-merging approaches are classified based on their working mechanism or the type of features they deal with. The concepts and characteristics of these map-merging methods are elaborated in this review. The contents summarized in this paper provide insights and guidance for future multiple-ground-robot SLAM solutions.

scholarly journals The Characteristics of the Map Merging Methods: A Survey

2010 ◽  
Vol 41 (1) ◽  
pp. 113-121 ◽  
Author(s):  
Ilze Andersone
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
Research Field ◽  
Autonomous Mobile Robots ◽  
Multiple Robots ◽  
Characteristic Set ◽  
Robotic Mapping ◽  
New Research ◽  
Multi Robot ◽  
Map Merging

The Characteristics of the Map Merging Methods: A SurveyThe development of the autonomous mobile robots is a popular field of research in the artificial intelligence for more than twenty years. An important prerequisite for creation of autonomous robot is the ability to create a map of the environment. However there are several problems in the robotic mapping that are still not completely solved. The use of multiple robots for mapping solves some of these problems, but in this case several new problems, specific to multi-robot mapping, arise. One of the problems in multi-robot mapping is merging all of the local maps that robots have created into one global map. The application of the robot teams in the exploration is a relatively new research field and initially methods for multi-robot mapping were just extended single robot mapping methods. Consequently the map merging problem was simplified. The research of map merging has only recently evolved, thus existing papers on the map merging describe specific map merging methods and there are no comprehensive surveys on the state of the art in the field of map merging. Therefore the goal of this paper is to describe the situation in the field of the map merging and to identify the main characteristics of the map merging methods. The interrelations of these characteristics can then be identified and the corresponding map merging approaches of each characteristic set named.

scholarly journals The influence of the map merging order on the resulting global map in multi-robot mapping

2012 ◽  
Vol 13 (1) ◽  
pp. 22-28
Author(s):  
Ilze Andersone
Keyword(s):  
Autonomous Robot ◽  
Multiple Robots ◽  
Important Prerequisite ◽  
Robot Teams ◽  
Mapping Process ◽  
As If ◽  
Multi Robot ◽  
Map Merging

An important prerequisite for creation of an autonomous robot is the ability to create the map of the environment. While the use of robot teams becomes more and more widely used, the issue of robot coordination becomes one of the central questions to be addressed. If multiple robots are used for the exploration of the environment, their collected information has to be fused into one general global map. This problem is called map merging. In the case, when more than two robots map the environment, it is possible that the order of map merging can influence the quality of the result - the global map. However, most researches in the map merging field address the problem as if the recommended order of map merging were known. The goal of this paper is to prove that the merging order can greatly influence the resulting global map and discuss the consequences this knowledge makes in the mapping process.

scholarly journals Port-Hamiltonian based teleoperation of a multi-robot system on periodic trajectories

2015 ◽  
Vol 48 (13) ◽  
pp. 69-74
Author(s):  
C. Secchi ◽  
L. Sabattini ◽  
C. Fantuzzi
Keyword(s):  
Robot System ◽  
Periodic Trajectories ◽  
Multi Robot

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.

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