Distributed Multirobot Exploration Based on Scene Partitioning and Frontier Selection

Lopez-Perez, Jose J.; Hernandez-Belmonte, Uriel H.; Ramirez-Paredes, Juan-Pablo; Contreras-Cruz, Marco A.; Ayala-Ramírez, Víctor

doi:10.1155/2018/2373642

Cited by 15 publications

(10 citation statements)

References 27 publications

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“…One more group of techniques for solving the exploration problem is clustering (also called partitioning). The approach can be applied as a single solution [30], [31] or paired with some other algorithms. For example, Sharma et al [18] implemented the multi-robot exploration using clustering with nature-inspired techniques.…”

Section: Related Workmentioning

confidence: 99%

Waypoint Mobile Robot Exploration Based on Biologically Inspired Algorithms

2020

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This paper proposes stochastic exploration algorithms for mobile robot exploration problems. Navigation with uncertain conditions in the absence of initial parameters is a situation wherein precomputation and prediction are impossible for a robot. Therefore, stochastic optimization techniques were applied to find the optimal solution for the robot exploration problem. Driving to the unknown areas, the robot updates the frontier line of sensor visibility during the exploration mission. The points of the frontier line are assumed as the swarm population with their own positions and costs, which allows the computation of the next global waypoint. The calculation of global waypoints is carried out by a nature-inspired optimization algorithm that can place a waypoint in uncertainties. This study offers to apply three metaheuristic algorithms individually, such as Whale Optimization, Grey Wolf Optimizer, and Particle Swarm Optimization algorithms, for comparison and testing their performances in the mobile robotics. At first, the simulations based on the proposed exploration algorithms were implemented and evaluated in a created environment. The results were compared in a single and average cases. Then, the real-world experiments using Grey Wolf Optimizer exploration algorithm were conducted in the different types of environments using MATLAB-ROS integration tool. These results proved the effectiveness and applicability of the bio-inspired optimization algorithm in the mobile robotics.

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Section: Related Workmentioning

confidence: 99%

Waypoint Mobile Robot Exploration Based on Biologically Inspired Algorithms

2020

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“…Arezoumand, Mashohor and Marhaban, came up with an another segmentation approach which aimed at finding objects in exploration mission [19]. Lopez-Perez et al [20] proposed idea of splitting of the scene by assigning frontiers their weights for each robot to explore different regions.…”

Section: Distributed Approachesmentioning

confidence: 99%

Multi-Robot Exploration in Unstructured and Dynamic Environments

Javed¹,

Khan²,

Ahmad³

2020

IJEW

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This paper deals with exploration by team of multirobots in unknown, unstructured and dynamic environments at the same time. The goal of the research is to minimize the total exploration time taken by team of robots to complete the mission and to achieve faster re-planning of their planned path in case of sudden changes in the environment as robots move through the environment. The proposed exploration approach is fully distributive in the sense that all robots are assigned separate regions in an unknown environment with each robot exploring its assigned region. As a first step the environment is partitioned into different regions as available number of robots and then each robot in a team is assigned its separate region for exploration. The proposed approach has been tested in different simulation environments with varying number of robots. Comparison with another approach proves the superiority of the approach in terms of reduction of exploration time in unstructured and changing environments.

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“…Lately, frontier exploration has also been applied to multirobot exploration establishing a routing priority for the frontiers and the robots [30]. Other works with multirobot frontier exploration have also added semantic and scene information to the decision process in order to separate the trajectories of the robots [31] or to obtain a higher reward of certain kind of areas [32]. However, these methods only used semantic information for the exploration process and built grid maps where these information is not included.…”

Section: Related Workmentioning

confidence: 99%

Topological Frontier-Based Exploration and Map-Building Using Semantic Information

Gómez

Hernandez

Barber

2019

Sensors

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Exploration of unknown environments is a fundamental problem in autonomous robotics that deals with the complexity of autonomously traversing an unknown area while acquiring the most important information of the environment. In this work, a mobile robot exploration algorithm for indoor environments is proposed. It combines frontier-based concepts with behavior-based strategies in order to build a topological representation of the environment. Frontier-based approaches assume that, to gain the most information of an environment, the robot has to move to the regions on the boundary between open space and unexplored space. The novelty of this work is in the semantic frontier classification and frontier selection according to a cost–utility function. In addition, a probabilistic loop closure algorithm is proposed to solve cyclic situations. The system outputs a topological map of the free areas of the environment for further navigation. Finally, simulated and real-world experiments have been carried out, their results and the comparison to other state-of-the-art algorithms show the feasibility of the exploration algorithm proposed and the improvement that it offers with regards to execution time and travelled distance.

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Distributed Multirobot Exploration Based on Scene Partitioning and Frontier Selection

Cited by 15 publications

References 27 publications

Waypoint Mobile Robot Exploration Based on Biologically Inspired Algorithms

Waypoint Mobile Robot Exploration Based on Biologically Inspired Algorithms

Multi-Robot Exploration in Unstructured and Dynamic Environments

Topological Frontier-Based Exploration and Map-Building Using Semantic Information

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