This research introduces the design and implementation of a universal systematic 2-dimensional terrain marking and coverage solution. Real world applications such as lawn mowing, mine detection, chemical spill clean-up, and humanitarian search and rescue missions can be automated by employing swarms of autonomous mobile robots to complete the task. In most of these real world applications, efficiency is of utmost importance especially when human lives are involved. The solution proposed builds up on two graph traversal algorithms; Depth First Search (DFS) and Breadth First Search (BFS), where the algorithms are adapted and modified to be utilized for coverage of 2-dimensional isometric grid-like representations of terrains. The solution is developed so that each robot in the swarm would be fully capable of covering and marking any terrain by itself. The efficiency of the solution is optimized by increasing the swarm size, as robots benefit from data sharing in their path planning and self organization within the terrain. Communication between robots enable them to perform on a higher level by benefiting from the collaborative distributed behavior of the swarm as a whole. The communication between particles is decentralized and is carried out at a local level with no need for a central guidance mechanism. Robot abilities in this research are limited, where a robot can see and move only to locations that are adjacent to its current location. A simulation based evaluation is conducted in this research to assess the robots’ area coverage and marking performance. The results show that the simulated robot swarm systems are suited for efficient flat area coverage, allowing for redundancy in data collection, and tolerating individual robot errors and shortcomings as the number of robots becomes more abundant.
Universal 2-Dimensional Terrain Marking for Autonomous Robot Swarms
2020-07-01
2258151 byte
Conference paper
Electronic Resource
English
NTRS | 2005
|Autonomous and Autonomic Swarms
NTRS | 2005
|Autonomous and Autonomic Swarms
NTIS | 2005
|