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Neural dynamics based complete grid coverage by single and multiple mobile robots. SN APPLIED SCIENCES 2021. [DOI: 10.1007/s42452-021-04508-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Abstract
AbstractNavigation of mobile robots in a grid based environment is useful in applications like warehouse automation. The environment comprises of a number of free grid cells for navigation and remaining grid cells are occupied by obstacles and/or other mobile robots. Such obstructions impose situations of collisions and dead-end. In this work, a neural dynamics based algorithm is proposed for complete coverage of a grid based environment while addressing collision avoidance and dead-end situations. The relative heading of the mobile robot with respect to the neighbouring grid cells is considered to calculate the neural activity. Moreover, diagonal movement of the mobile robot through inter grid cells is restricted to ensure safety from the collision with obstacles and other mobile robots. The circumstances where the proposed algorithm will fail to provide completeness are also discussed along with the possible ways to overcome those situations. Simulation results are presented to show the effectiveness of the proposed algorithm for a single and multiple mobile robots. Moreover, comparative studies illustrate improvements over other algorithms on collision free effective path planning of mobile robots within a grid based environment.
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Dutta A, Bhattacharya A, Kreidl OP, Ghosh A, Dasgupta P. Multi-robot informative path planning in unknown environments through continuous region partitioning. INT J ADV ROBOT SYST 2020. [DOI: 10.1177/1729881420970461] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
We consider the NP-hard problem of multirobot informative path planning in the presence of communication constraints, where the objective is to collect higher amounts of information of an ambient phenomenon. We propose a novel approach that uses continuous region partitioning into Voronoi components to efficiently divide an initially unknown environment among the robots based on newly discovered obstacles enabling improved load balancing between robots. Simulation results show that our proposed approach is successful in reducing the initial imbalance of the robots’ allocated free regions while ensuring close-to-reality spatial modeling within a reasonable amount of time.
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Affiliation(s)
- Ayan Dutta
- School of Computing, University of North Florida, Jacksonville, FL, USA
| | | | - O Patrick Kreidl
- School of Computing, University of North Florida, Jacksonville, FL, USA
- School of Engineering, University of North Florida, Jacksonville, FL, USA
| | - Anirban Ghosh
- School of Computing, University of North Florida, Jacksonville, FL, USA
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