In this paper we present an approach to autonomous exploration of a rescue environment. Exploration is based on unexplored frontiers and navigation on a two-level approach to the robot motion problem. Our method makes use of a motion planner capable of negotiating with very fine representations of the environment, that is used to move in a cluttered scenario. A topological path-planner "guides" the lower level and reduces the search space. The two algorithms are derived from two widely-used probabilistic algorithms, currently successfully deployed in many robot applications, the Probabilistic RoadMap and the Rapid-exploring Random Trees; however, their adaptation to the rescue scenario requires significant extensions. © 2005 IEEE.
In this paper we present an approach to autonomous exploration of a rescue environment. Exploration is based on unexplored frontiers and navigation on a two-level approach to the robot motion problem. Our method makes use of a motion planner capable of negotiating with very fine representations of the environment, that is used to move in a cluttered scenario. A topological path-planner "guides" the lower level and reduces the search space. The two algorithms are derived from two widely-used probabilistic algorithms, currently successfully deployed in many robot applications, the Probabilistic RoadMap and the Rapid-exploring Random Trees; however, their adaptation to the rescue scenario requires significant extensions.
Autonomous navigation and exploration in a rescue environment / Calisi, Daniele; Farinelli, Alessandro; Iocchi, Luca; Nardi, Daniele. - 2005:(2005), pp. 54-59. (Intervento presentato al convegno 2005 IEEE International Workshop on Safety, Security and Rescue Robotics tenutosi a Kobe; Japan nel JUN 06-09, 2005) [10.1109/SSRR.2005.1501268].
Autonomous navigation and exploration in a rescue environment
CALISI, daniele;FARINELLI, ALESSANDRO;IOCCHI, Luca;NARDI, Daniele
2005
Abstract
In this paper we present an approach to autonomous exploration of a rescue environment. Exploration is based on unexplored frontiers and navigation on a two-level approach to the robot motion problem. Our method makes use of a motion planner capable of negotiating with very fine representations of the environment, that is used to move in a cluttered scenario. A topological path-planner "guides" the lower level and reduces the search space. The two algorithms are derived from two widely-used probabilistic algorithms, currently successfully deployed in many robot applications, the Probabilistic RoadMap and the Rapid-exploring Random Trees; however, their adaptation to the rescue scenario requires significant extensions. © 2005 IEEE.| File | Dimensione | Formato | |
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