A PSO-Inspired Multi-Robot Map Exploration Algorithm Using Frontier-Based Strategy

2013 ◽  
Vol 2 (2) ◽  
pp. 1-13 ◽  
Author(s):  
Yi Zhou ◽  
Kai Xiao ◽  
Yiheng Wang ◽  
Alei Liang ◽  
Aboul Ella Hassanien
Keyword(s):  
Mobile Robots ◽  
Distributed Algorithm ◽  
Fundamental Problem ◽  
Local Area ◽  
Autonomous Mobile Robots ◽  
Swarm Optimization ◽  
Exploration Time ◽  
Real Robot ◽  
Exploration Task ◽  
Unknown Region

Map exploration is a fundamental problem in mobile robots. This paper presents a distributed algorithm that coordinates a team of autonomous mobile robots to explore an unknown environment. The proposed strategy is based on frontiers which are the regions on the boundary between open and unexplored space. With this strategy, robots are guided to move constantly to the nearest frontier to reduce the size of unknown region. Based on the Particle Swarm Optimization (PSO) model incorporated in the algorithm, robots are navigated towards remote frontier after exploring the local area. The exploration completes when there is no frontier cell in the environment. The experiments implemented on both simulated and real robot scenarios show that the proposed algorithm is capable of completing the exploration task. Compared to the conventional method of randomly selecting frontier, the proposed algorithm proves its efficiency by the decreased 60% exploration time at least. Additional experimental results show the decreased coverage time when the number of robots increases, which further suggests the validity, efficiency and scalability.

A PSO-Inspired Multi-Robot Map Exploration Algorithm Using Frontier-Based Strategy

2019 ◽  
pp. 362-375 ◽  
Author(s):  
Yi Zhou ◽  
Kai Xiao ◽  
Yiheng Wang ◽  
Alei Liang ◽  
Aboul Ella Hassanien
Keyword(s):  
Particle Swarm Optimization ◽  
Mobile Robots ◽  
Distributed Algorithm ◽  
Fundamental Problem ◽  
Local Area ◽  
Swarm Optimization ◽  
Exploration Time ◽  
Real Robot ◽  
Exploration Task ◽  
Unknown Region

Map exploration is a fundamental problem in mobile robots. This paper presents a distributed algorithm that coordinates a team of autonomous mobile robots to explore an unknown environment. The proposed strategy is based on frontiers which are the regions on the boundary between open and unexplored space. With this strategy, robots are guided to move constantly to the nearest frontier to reduce the size of unknown region. Based on the Particle Swarm Optimization (PSO) model incorporated in the algorithm, robots are navigated towards remote frontier after exploring the local area. The exploration completes when there is no frontier cell in the environment. The experiments implemented on both simulated and real robot scenarios show that the proposed algorithm is capable of completing the exploration task. Compared to the conventional method of randomly selecting frontier, the proposed algorithm proves its efficiency by the decreased 60% exploration time at least. Additional experimental results show the decreased coverage time when the number of robots increases, which further suggests the validity, efficiency and scalability.

The Second Stage Experiments on Long Term Activity of Autonomous Mobile Robots - Repetitive Navigation for One Week in a Corridor

2002 ◽  
Vol 14 (4) ◽  
pp. 375-381
Author(s):  
Yasushi Hada ◽  
◽  
Shin'ichi Yuta
Keyword(s):  
Mobile Robots ◽  
Experimental System ◽  
Autonomous Mobile Robots ◽  
Second Stage ◽  
Real Robot

Our goal is to enhance the autonomy of mobile robots, which must perform meaningful tasks for a long-term with regular maintenance at intervals of a week or month. Since we started this research, we recognize not only complexity but duration as indications of autonomy, which we call ""Long Term Activity"". We are studying such autonomy using an experimental robotics approach, which constructs a real robot and develops required technologies. Our experimental system, still in work, navigates a corridor environment autonomously for one week. In this paper, we present the system and some results of experiments.

Optimization-based formation of autonomous mobile robots

Robotica ◽  
2010 ◽  
Vol 29 (4) ◽  
pp. 515-525 ◽  
Author(s):  
Huan Zhang ◽  
Pubudu N. Pathirana
Keyword(s):  
Mobile Robots ◽  
Formation Control ◽  
Fundamental Problem ◽  
Optimization Techniques ◽  
Autonomous Mobile Robots ◽  
Coordinate Systems ◽  
Geometric Pattern ◽  
Difference Function ◽  
Movement Strategy ◽  
Robot Configuration

SUMMARYThe formation of autonomous mobile robots to an arbitrary geometric pattern in a distributed fashion is a fundamental problem in formation control. This paper presents a new asynchronous, memoryless (oblivious) algorithm to the formation problem via distributed optimization techniques. The optimization minimizes an appropriately defined difference function between the current robot distribution and the target geometric pattern. The optimization processes are performed independently by individual robots in their local coordinate systems. A movement strategy derived from the results of the distributed optimizations guarantees that every movement makes the current robot configuration approaches the target geometric pattern until the final pattern is reached.

Surrounding Robots – A Discrete Localized Solution for the Intruder Problem –

2014 ◽  
Vol 18 (3) ◽  
pp. 315-319 ◽  
Author(s):  
László Blázovics ◽  
◽  
Tamás Lukovszki ◽  
Bertalan Forstner ◽  
Keyword(s):  
Mobile Robots ◽  
Finite Time ◽  
Distributed Algorithm ◽  
Autonomous Mobile Robots ◽  
Cooperative Robotics ◽  
The Past ◽  
Decentralized Algorithms

Decentralized algorithms are often used in the cooperative robotics field, especially by large swarm systems. We present a distributed algorithm for a problem in which a group of autonomous mobile robots must surround a given target. These robots are oblivious, i.e., they have no memory of the past. They use only local sensing and need no dedicated communication among themselves. We introduce, then solve the problem in which the group of autonomous mobile robots must surround a given target – we call it the “discrete multiorbit target surrounding problem” (DMTSP). We evaluate our solution using simulation and prove that our solution invariably ensures that robots enclose the target in finite time.

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