2005 (English)In: Robotics Research: The Eleventh International Symposium, Springer Berlin/Heidelberg, 2005, 57-59 p.Chapter in book (Refereed)
While the current part carries the title “path planning” the contributions in this section cover two topics: mapping and planning. In some sense one might argue that intelligent (autonomous) mapping actually requires path planning. While this is correct the contributions actually have a broader scope as is outlined below. A common theme to all of the presentations in this section is the adoption of hybrid representations to facilitate efficient processing in complex environments. Purely geometric models allow for accurate estimation of position and motion generation, but they scale poorly with environmental complexity while qualitative geometric models have a limited accuracy and are well suited for global estimation of trajectories/locations. Through fusion of qualitative and quantitative models it becomes possible to develop systems that have tractable complexity while maintaining geometric accuracy.
Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2005. 57-59 p.
, Springer Tracts in Advanced Robotics, ISSN 1610-7438 ; Volume 15
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:kth:diva-148478DOI: 10.1007/11008941_6ScopusID: 2-s2.0-84885041179ISBN: 978-3-540-23214-8ISBN: 978-3-540-31508-7OAI: oai:DiVA.org:kth-148478DiVA: diva2:751028
QC 201409302014-09-302014-08-082014-09-30Bibliographically approved