Autonomous Exploration and Motion Planning for an Unmanned Aerial Vehicle Navigating Rivers. Issue 8 (8th June 2015)
- Record Type:
- Journal Article
- Title:
- Autonomous Exploration and Motion Planning for an Unmanned Aerial Vehicle Navigating Rivers. Issue 8 (8th June 2015)
- Main Title:
- Autonomous Exploration and Motion Planning for an Unmanned Aerial Vehicle Navigating Rivers
- Authors:
- Nuske, Stephen
Choudhury, Sanjiban
Jain, Sezal
Chambers, Andrew
Yoder, Luke
Scherer, Sebastian
Chamberlain, Lyle
Cover, Hugh
Singh, Sanjiv - Abstract:
- Abstract : Mapping a river's geometry provides valuable information to help understand the topology and health of an environment and deduce other attributes such as which types of surface vessels could traverse the river. While many rivers can be mapped from satellite imagery, smaller rivers that pass through dense vegetation are occluded. We develop a micro air vehicle (MAV) that operates beneath the tree line, detects and maps the river, and plans paths around three‐dimensional (3D) obstacles (such as overhanging tree branches) to navigate rivers purely with onboard sensing, with no GPS and no prior map. We present the two enabling algorithms for exploration and for 3D motion planning. We extract high‐level goal‐points using a novel exploration algorithm that uses multiple layers of information to maximize the length of the river that is explored during a mission. We also present an efficient modification to the SPARTAN (Sparse Tangential Network) algorithm called SPARTAN‐lite, which exploits geodesic properties on smooth manifolds of a tangential surface around obstacles to plan rapidly through free space. Using limited onboard resources, the exploration and planning algorithms together compute trajectories through complex unstructured and unknown terrain, a capability rarely demonstrated by flying vehicles operating over rivers or over ground. We evaluate our approach against commonly employed algorithms and compare guidance decisions made by our system to those made byAbstract : Mapping a river's geometry provides valuable information to help understand the topology and health of an environment and deduce other attributes such as which types of surface vessels could traverse the river. While many rivers can be mapped from satellite imagery, smaller rivers that pass through dense vegetation are occluded. We develop a micro air vehicle (MAV) that operates beneath the tree line, detects and maps the river, and plans paths around three‐dimensional (3D) obstacles (such as overhanging tree branches) to navigate rivers purely with onboard sensing, with no GPS and no prior map. We present the two enabling algorithms for exploration and for 3D motion planning. We extract high‐level goal‐points using a novel exploration algorithm that uses multiple layers of information to maximize the length of the river that is explored during a mission. We also present an efficient modification to the SPARTAN (Sparse Tangential Network) algorithm called SPARTAN‐lite, which exploits geodesic properties on smooth manifolds of a tangential surface around obstacles to plan rapidly through free space. Using limited onboard resources, the exploration and planning algorithms together compute trajectories through complex unstructured and unknown terrain, a capability rarely demonstrated by flying vehicles operating over rivers or over ground. We evaluate our approach against commonly employed algorithms and compare guidance decisions made by our system to those made by a human piloting a boat carrying our system over multiple kilometers. We also present fully autonomous flights on riverine environments generating 3D maps over several hundred‐meter stretches of tight winding rivers. … (more)
- Is Part Of:
- Journal of field robotics. Volume 32:Issue 8(2015)
- Journal:
- Journal of field robotics
- Issue:
- Volume 32:Issue 8(2015)
- Issue Display:
- Volume 32, Issue 8 (2015)
- Year:
- 2015
- Volume:
- 32
- Issue:
- 8
- Issue Sort Value:
- 2015-0032-0008-0000
- Page Start:
- 1141
- Page End:
- 1162
- Publication Date:
- 2015-06-08
- Subjects:
- Robots, Industrial -- Periodicals
Automatic control -- Periodicals
629.892 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1556-4967 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/rob.21596 ↗
- Languages:
- English
- ISSNs:
- 1556-4959
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4984.130000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 1141.xml