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• W3207369576 abstract "In unstructured and unknown environments, heterogeneous robots must be able to perceive the environment, coordinate with each other and complete tasks collaboratively with onboard sensors. In this paper, a tightly-coupled perception and navigation framework is proposed for heterogeneous land-air robots, which forms a closed loop of perception-navigation for heterogeneous robots. The key novelty of this work is the proposing of a unified framework to formulate the cooperative mapping and navigation problem, as well as the derivation of high-level coordination strategy and low-level goal-oriented navigation within a fully integrated approach. To provide a comprehensive understanding of the environment, a flexible probabilistic map fusion algorithm is applied to merge local maps generated by hybrid robots. The proposed UAV-UGV hybrid system is validated in challenging experiments, proving its robustness and effectiveness in practical tasks." @default.
• W3207369576 created "2021-10-25" @default.
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• W3207369576 date "2021-05-30" @default.
• W3207369576 modified "2023-10-06" @default.
• W3207369576 title "Tightly-Coupled Perception and Navigation of Heterogeneous Land-Air Robots in Complex Scenarios" @default.
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• W3207369576 doi "https://doi.org/10.1109/icra48506.2021.9562042" @default.
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