Frontier Based Multi Robot Area Exploration Using Prioritized Routing

Sharma, Karan; Honc, Daniel; Dušek, František; Kumar, T. Gireesh

doi:10.7148/2016-0025

Cited by 8 publications

(6 citation statements)

References 7 publications

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“…They showed higher performance than standard frontier-based exploration for big indoor environments. 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].…”

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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Section: Related Workmentioning

confidence: 99%

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

Gómez

Hernandez

Barber

2019

Sensors

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“…In map synchronization, agents can form into subgroups that are close enough to have the same map, while other agents that are not will synchronize maps when they approach [12]. This is also similar to Frontier based, which is concerned with exploring all points of a grid area in a minimum amount of time [13,14]. However, these do not consider load balancing the work of the agents as we do here.…”

Section: Related Workmentioning

confidence: 99%

Balanced Parallel Exploration of Orthogonal Regions

Clements

Busch

et al. 2019

Algorithms

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We consider the use of multiple mobile agents to explore an unknown area. The area is orthogonal, such that all perimeter lines run both vertically and horizontally. The area may consist of unknown rectangular holes which are non-traversable internally. For the sake of analysis, we assume that the area is discretized into N points allowing the agents to move from one point to an adjacent one. Mobile agents communicate through face-to-face communication when in adjacent points. The objective of exploration is to develop an online algorithm that will explore the entire area while reducing the total work of all k agents, where the work is measured as the number of points traversed. We propose splitting the exploration into two alternating tasks, perimeter and room exploration. The agents all begin with the perimeter scan and when a room is found they transition to room scan after which they continue with perimeter scan until the next room is found and so on. Given the total traversable points N, our algorithm completes in total O ( N ) work with each agent performing O ( N / k ) work, namely the work is balanced. If the rooms are hole-free the exploration time is also asymptotically optimal, O ( N / k ) . To our knowledge, this is the first agent coordination algorithm that considers simultaneously work balancing and small exploration time.

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“…The work in [11] is a centralized area exploration for autonomous agents, with an unknown environment and static obstacles. A reasoning algorithm is proposed which is based on routing priority.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Distributed Multirobot Exploration Based on Scene Partitioning and Frontier Selection

Lopez-Perez

Hernandez-Belmonte

Ramirez-Paredes

et al. 2018

Mathematical Problems in Engineering

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In mobile robotics, the exploration task consists of navigating through an unknown environment and building a representation of it. The mobile robot community has developed many approaches to solve this problem. These methods are mainly based on two key ideas. The first one is the selection of promising regions to explore and the second is the minimization of a cost function involving the distance traveled by the robots, the time it takes for them to finish the exploration, and others. An option to solve the exploration problem is the use of multiple robots to reduce the time needed for the task and to add fault tolerance to the system. We propose a new method to explore unknown areas, by using a scene partitioning scheme and assigning weights to the frontiers between explored and unknown areas. Energy consumption is always a concern during the exploration, for this reason our method is a distributed algorithm, which helps to reduce the number of communications between robots. By using this approach, we also effectively reduce the time needed to explore unknown regions and the distance traveled by each robot. We performed comparisons of our approach with state-of-the-art methods, obtaining a visible advantage over other works.

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Frontier Based Multi Robot Area Exploration Using Prioritized Routing

Cited by 8 publications

References 7 publications

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

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

Balanced Parallel Exploration of Orthogonal Regions

Distributed Multirobot Exploration Based on Scene Partitioning and Frontier Selection

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