Efficient Autonomous Exploration Planning of Large-Scale 3-D Environments
| Autor: | Fredrik Heintz, Mattias Tiger, Magnus Selin, Patric Jensfelt, Daniel Duberg |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Control and Optimization Computer science Distributed computing Biomedical Engineering 02 engineering and technology 020901 industrial engineering & automation Datorseende och robotik (autonoma system) Artificial Intelligence 0202 electrical engineering electronic engineering information engineering Motion and Path Planning Motion planning Computer Vision and Robotics (Autonomous Systems) business.industry Mechanical Engineering Mobile robot Robotics Search and Rescue Robots Computer Science Applications Human-Computer Interaction Mapping Control and Systems Engineering 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition Artificial intelligence business Scale (map) |
| Zdroj: | IEEE Robotics and Automation Letters. 4:1699-1706 |
| ISSN: | 2377-3774 |
| DOI: | 10.1109/lra.2019.2897343 |
| Popis: | Exploration is an important aspect of robotics, whether it is for mapping, rescue missions or path planning in an unknown environment. Frontier Exploration planning (FEP) and Receding Horizon Next-Best-View planning (RH-NBVP) are two different approaches with different strengths and weaknesses. FEP explores a large environment consisting of separate regions with ease, but is slow at reaching full exploration due to moving back and forth between regions. RH-NBVP shows great potential and efficiently explores individual regions, but has the disadvantage that it can get stuck in large environments not exploring all regions. In this work we present a method that combines both approaches, with FEP as a global exploration planner and RH-NBVP for local exploration. We also present techniques to estimate potential information gain faster, to cache previously estimated gains and to exploit these to efficiently estimate new queries. FACT (SSF) WASP |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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