Abstract
Efficient exploration of unknown environments is a fundamental problem in mobile robotics. We propose a novel topological map whose nodes are represented with the range finder's free beams together with the visual scale-invariant features. The topological map enables teams of robots to efficiently explore environments from different, unknown locations without knowing their initial poses, relative poses and global poses in a certain world reference frame. The experiments of map merging and coordinated exploration demonstrate the proposed map is not only easy for merging, but also convenient for robust and efficient explorations in unknown environments.
Highlights
There is growing interest in using groups of coordinating autonomous robots to perform such tasks as reconnaissance, rescue and hazard identification due to the fact that the cooperative robots promise the immediate advantages of parallelism, redundancy and fault tolerance (O’Berine, D. & Schukat, M., 2005)
Considering the challenges in the coordinated exploration, the advantages and drawbacks of the different map presentations, we propose a novel topological map whose nodes are represented with the range finder’s free beams together with the visual scaleinvariant features
Different from these market-based approaches based on metric map, the target points/commodities used in our experiments are detectable nodes rather than the global position of the frontier points, which means the global localization and the initial pose of each robot in a certain world reference frame are not necessary during the course of exploration
Summary
There is growing interest in using groups of coordinating autonomous robots to perform such tasks as reconnaissance, rescue and hazard identification due to the fact that the cooperative robots promise the immediate advantages of parallelism, redundancy and fault tolerance (O’Berine, D. & Schukat, M., 2005). & Saffiotti, A., 2002) extract the topological map from the grid by analyzing the shape of free space by means of the mathematical morphology image processing tool. This hierarchical approach still has the problem of large memory requirement involved in a grid map. Thrun et al split free space into homogeneous regions according to region shape criteria Their topological map is constructed off-line and only when a fully explored metric map is available Considering the challenges in the coordinated exploration, the advantages and drawbacks of the different map presentations, we propose a novel topological map whose nodes are represented with the range finder’s free beams together with the visual scaleinvariant features.
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