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Autonomous navigation in real-world industrial environments is a challenging task in many respects. One of the key open challenges is fast planning and execution of trajectories to reach arbitrary target positions and orientations with high accuracy and precision, while taking into account non-holonomic vehicle constraints. In recent years, lattice-based motion planners have been successfully used...
Industrial environments are rarely static and often their configuration is continuously changing due to the material transfer flow. This is a major challenge for infrastructure free localization systems. In this paper we address this challenge by introducing a localization approach that uses a dual-timescale approach. The proposed approach — Dual-Timescale Normal Distributions Transform Monte Carlo...
Autonomous vehicles operating in real-world industrial environments have to overcome numerous challenges, chief among which is the creation and maintenance of consistent 3D world models. This paper proposes to address the challenges of online real-world mapping by building upon previous work on compact spatial representation and formulating a novel 3D mapping approach — the Normal Distributions Transform...
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