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Multi Layered Maps for Enhanced Environmental Perception
Linköping University, Department of Management and Engineering, Fluid and Mechatronic Systems. Linköping University, The Institute of Technology.
Scania CV AB.
2011 (English)Conference paper (Other academic)
Abstract [en]

Traditionally, an in-vehicle map consists of only one type of data, tailored for a single user function. For example, the navigation maps contain spatial information about the roads. On the other hand, a map built for adaptive cruise control use consists of the detected vehicles and their properties. In autonomous vehicle research, the maps are often built up as an occupancy grid where areas are classified as passable or impassable. Using these kinds of maps separately, however, is not enough to support the traffic safety enhancing and advanced driver assistance systems of today and tomorrow.

Instead of using separate systems to handle individual safety or planning tasks, information could be stored in one shared map containing several correlated layers of information. Map information can be collected by any number of different sensor devices, and fusion algorithms can be used to enhance the quality of the information. User functions that base their decisions on the multi-layered map can then retrieve any subset of the stored information making them scalable in terms of processor and memory use.

The advantages of using a shared multi-layer spatial data storage are several:

Sensors and user functions are decoupled. This can make it easier and more cost efficient to implement additional functions.

Data quality is enhanced. Since fusion techniques can be used to generate estimates of physical properties from several sensors, the fused data is based on all available information.

Using models that describe a certain entity, properties that are not even measured can be estimated by the system.

This work describes an experimental semi-autonomous ground vehicle system, where on-line generated maps containing multiple layers of information are used for obstacle avoidance and planning of a suitable path between waypoints. The system is primarily simulated using physical vehicle models in a suitable environment, but limited real-world experiments with a subset of functions are also performed. 

Place, publisher, year, edition, pages
2011. 2244- p.
National Category
Robotics Vehicle Engineering
URN: urn:nbn:se:liu:diva-70851DOI: 10.4271/2011-01-2244OAI: diva2:442132
SAE 2011 Commercial Vehicle Engineering Congress, 13-14 September 2011, Rosemont, Illinois USA
Available from: 2011-09-20 Created: 2011-09-20 Last updated: 2012-12-03Bibliographically approved
In thesis
1. Mobile Robot Traversability Mapping: For Outdoor Navigation
Open this publication in new window or tab >>Mobile Robot Traversability Mapping: For Outdoor Navigation
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

To avoid getting stuck or causing damage to a vehicle or its surroundings a driver must be able to identify obstacles and adapt speed to ground conditions. An automatically controlled vehicle must be able to handle these identifications and adjustments by itself using sensors, actuators and control software. By storing properties of the surroundings in a map, a vehicle revisiting an area can benefit from prior information.

Rough ground may cause oscillations in the vehicle chassis. These can be measured by on-board motion sensors. For obstacle detection, a representation of the geometry of the surroundings can be created using range sensors. Information on where it is suitable to drive, called traversability, can be generated based on these kinds of sensor measurements.

In this work, real semi-autonomous mobile robots have been used to create traverasbility maps in both simulated and real outdoor environments. Seeking out problems through experiments and implementing algorithms in an attempt to solve them has been the core of the work.

Finding large obstacles in the vicinity of a vehicle is seldom a problem; accurately identifying small near-ground obstacles is much more difficult, however. The work additionally includes both high-level path planning, where no obstacle details are considered, and more detailed planning for finding an obstacle free path. How prior maps can be matched and merged in preparation for path planning operations is also shown. To prevent collisions with unforeseen objects, up-to-date traversability information is used in local-area navigation and obstacle avoidance.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. 122 p.
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1564
Traversability, Laser, Roughness, Mapping, Planning, Mobile robot, Navigation, Implementation
National Category
Engineering and Technology
urn:nbn:se:liu:diva-85937 (URN)LIU-TEK-LIC-2012:49 (Local ID)978-91-7519-726-5 (ISBN)LIU-TEK-LIC-2012:49 (Archive number)LIU-TEK-LIC-2012:49 (OAI)
2012-12-14, A39, A-huset, Campus Valla, Linköpings universitet, Linköping, 14:15 (English)
Available from: 2012-12-03 Created: 2012-12-03 Last updated: 2012-12-06Bibliographically approved

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