Mapping under changing trajectory estimates
| Autor: | Martin Llofriu, Philip Fong, Mario E. Munich, Vazgen Karapetyan |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
020901 industrial engineering & automation Occupancy business.industry Computer science 0202 electrical engineering electronic engineering information engineering Robot Navigation system 020201 artificial intelligence & image processing Computer vision 02 engineering and technology Artificial intelligence business |
| Zdroj: | IROS |
| DOI: | 10.1109/iros.2017.8202320 |
| Popis: | Occupancy mapping is an important component of a robot navigation system since it enables intelligent planning of actions to accomplish a task. In some cases, occupancy information is mapped as part of a SLAM system. In other cases, such as visual SLAM, an occupancy map must be separately created, harnessing localization information. We present a novel occupancy mapping method that adaptively and efficiently takes advantage of improved trajectory estimates from the localization system, without requiring storage of all poses of the trajectory or the sensor information from all poses. Occupancy information is stored in local maps anchored to poses in the trajectory. Local maps are created adaptively depending on the uncertainty of localization. The local maps maintain consistency of occupancy information independently of changes in the localization map due to loop closures or convergence of the estimation algorithm. At any time, a global occupancy map (snapshot map) can be rendered from the local occupancy maps. We evaluate the performance of the system using real data and compare it to two baseline methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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