Multi-Robot Graph Exploration and Map Building with Collision Avoidance: A Decentralized Approach

Nagavarapu, Sarat Chandra; Vachhani, Leena; Sinha, Arpita

doi:10.1007/s10846-015-0309-9

Cited by 16 publications

(8 citation statements)

References 14 publications

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“…iii. Graph-based maps: is described as a graph consists of edges and vertices, it represents the environment as an abstract model with intersected and integrated paths [4,12], iv. Semantic maps, is an abstract model that contains the relationships and functions of the objects in the environment This paper will concentrate on the cell-based map while performing the task.…”

Section: Environmentmentioning

confidence: 99%

“…Recently, MRS have been used in several applications such as military applications, search and rescue, surveillance, cleaning, and mine clearing, etc. [4]. In such applications, robots should make a decision whether to perform new tasks or establish cooperative interactions to achieve their individual and collective goals [4,5].…”

Section: Introductionmentioning

confidence: 99%

“…[4]. In such applications, robots should make a decision whether to perform new tasks or establish cooperative interactions to achieve their individual and collective goals [4,5]. Most of MRS applications depend primarily on the multi-robot exploration process to build an environment map.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Evaluation of Multi-Robot Systems Exploration Algorithms

Mohamed

Elshenawy

Harb

2019

Journal of Al-Azhar University Engineering Sector

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Multi-robot systems exploration of an environment is an important process that most automated applications depend on. In this paper, common algorithms used to perform the exploration process of an unknown cell-based environment occupied by a set of obstacles using a set of identical robots are studied and their performance are compared depending on three metrics: the total explored area in the map, overall mission time, and the number of hops in the networked robots. The performance of these algorithms is evaluated for different environments and different team sizes using MRESim computer simulator.

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Section: Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Evaluation of Multi-Robot Systems Exploration Algorithms

Mohamed

Elshenawy

Harb

2019

Journal of Al-Azhar University Engineering Sector

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“…Instead of depth data, Mori and Scherer (2013) calculated a relative size cue of the same object to detect and avoid frontal obstacles. Recently, novel approaches (Alejo et al , 2016; Nagavarapu et al , 2016) have been proposed for collision avoidance for multiple aerial robots. However, those approaches can handle only static obstacles, and the results are validated in only simulated cases.…”

Section: Related Workmentioning

confidence: 99%

Hybrid obstacle avoidance system with vision and ultrasonic sensors for multi-rotor MAVs

Zhou

Zou

Liu

2018

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Purpose This paper aims to develop an obstacle avoidance system for a multi-rotor micro aerial vehicle (MAV) that flies in indoor environments which usually contain transparent, texture-less or moving objects. Design/methodology/approach The system adopts a combination of a stereo camera and an ultrasonic sensor to detect obstacles and extracts three-dimensional (3D) point clouds. The obstacle map is built on a coarse global map and updated by local maps generated by the recent 3D point clouds. An efficient layered A* path planning algorithm is also proposed to address the path planning in 3D space for MAVs. Findings The authors conducted a lot of experiments in both static and dynamic scenes. The results show that the obstacle avoidance system works reliably even when transparent or texture-less obstacles are present. The layered A* path planning algorithm is much faster than the traditional 3D algorithm and makes the system response quickly when the obstacle map has been changed because of the moving objects. Research limitations/implications The limited field of view of both stereo camera and ultrasonic sensor makes the system need to change heading first before moving side to side or moving backward. But this problem could be addressed when multiple systems are mounted toward different directions on the MAV. Practical implications The developed approach could be valuable to applications in indoors. Originality/value This paper presents a robust obstacle avoidance system and a fast layered path planning algorithm that are easy to be implemented for practical systems.

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“…Note that in dynamic coverage or search, mobile sensors do not need to move together in a formation like in the sweep coverage. Note that, a search task may also be named as an area exploration task [126,190,17,25,35,76,108] in the mapping related topics or be called as a foraging strategy for animals [185,149].…”

Section: Complete Coverage and Searchmentioning

confidence: 99%

Decentralized Collision-Free Control of Multiple Robots in 2D and 3D Spaces

Yang

2017

Preprint

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Decentralized control of robots has attracted huge research interests. However, some of the research used unrealistic assumptions without collision avoidance. This report focuses on the collision-free control for multiple robots in both complete coverage and search tasks in 2D and 3D areas which are arbitrary unknown. All algorithms are decentralized as robots have limited abilities and they are mathematically proved.The report starts with the grid selection in the two tasks. Grid patterns simplify the representation of the area and robots only need to move straightly between neighbor vertices. For the 100% complete 2D coverage, the equilateral triangular grid is proposed. For the complete coverage ignoring the boundary effect, the grid with the fewest vertices is calculated in every situation for both 2D and 3D areas.The second part is for the complete coverage in 2D and 3D areas. A decentralized collision-free algorithm with the above selected grid is presented driving robots to sections which are furthest from the reference point. The area can be static or expanding, and the algorithm is simulated in MATLAB.Thirdly, three grid-based decentralized random algorithms with collision avoidance are provided to search targets in 2D or 3D areas. The number of targets can be known or unknown. In the first algorithm, robots choose vacant neighbors randomly with priorities on unvisited ones while the second one adds the repulsive force to disperse robots if they are close. In the third algorithm, if surrounded by visited vertices, the robot will use the breadth-first search algorithm to go to one of the nearest unvisited vertices via the grid. The second search algorithm is verified on Pioneer 3-DX robots. The general way to generate the formula to estimate the search time is demonstrated. Algorithms are compared with five other algorithms in MATLAB to show their effectiveness.

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Multi-Robot Graph Exploration and Map Building with Collision Avoidance: A Decentralized Approach

Cited by 16 publications

References 14 publications

An Evaluation of Multi-Robot Systems Exploration Algorithms

An Evaluation of Multi-Robot Systems Exploration Algorithms

Hybrid obstacle avoidance system with vision and ultrasonic sensors for multi-rotor MAVs

Decentralized Collision-Free Control of Multiple Robots in 2D and 3D Spaces

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