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Semantic Trajectory Planning for Long-Distant Unmanned Aerial Vehicle Navigation in Urban Environments
- Source :
- IROS, MIT web domain
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- © 2020 IEEE. There has been a considerable amount of recent work on high-speed micro-aerial vehicle flight in unknown and unstructured environments. Generally these approaches either use active sensing or fly slowly enough to ensure a safe braking distance with the relatively short sensing range of passive sensors. The former generally requires carrying large and heavy LIDARs and the latter only allows flight far away from the dynamic limits of the vehicle. One of the significant challenges for high-speed flight is the computational demand of trajectory planning at sufficiently high rates and length scales required in outdoor environments. We tackle both problems in this work by leveraging semantic information derived from an RGB camera on-board the vehicle. We first describe how to use semantic information to increase the effective range of perception on certain environment classes. Second, we present a sparse representation of the environment that is sufficiently lightweight for long distance path planning. We show how our approach outperforms more traditional metric planners which seek the shortest path, demonstrate the semantic planner's capabilities in a set of simulated and excessive real-world autonomous quadrotor flights in an urban environment.<br />Army Research Laboratory (Contract W911NF-17-2-0181)
- Subjects :
- 0209 industrial biotechnology
Computer science
Real-time computing
02 engineering and technology
Sparse approximation
Vehicle dynamics
Braking distance
020901 industrial engineering & automation
Shortest path problem
Metric (mathematics)
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Motion planning
Set (psychology)
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- Accession number :
- edsair.doi.dedup.....270c0c3bf01253834fa5cbbfcdaa2e68