Situational reasoning for road driving in an urban environment
Abstract
Robot navigation in urban environments requires situational reasoning. Given the complexity of the environment and the behavior specified by traffic rules, it is necessary to recognize the current situation to impose the correct traffic rules. In an attempt to manage the complexity of the situational reasoning subsystem, this paper describes a finite state machine model to govern the situational reasoning process. The logic state machine and its interaction with the planning system are discussed. The approach was implemented on Alice, Team Caltech's entry into the 2007 DARPA Urban Challenge. Results from the qualifying rounds are discussed. The approach is validated and the shortcomings of the implementation are identified.
Additional Information
© 2008 INSTICC Press. The work presented here is the culmination of many members of Team Caltech, especially: Vanessa Carson, Sven Gowal, Andrew Howard, Christian Looman. This work was supported in part by the Defense Advanced Research Projects Agency (DARPA) under contract HR0011-06-C-0146, the California Institute of Technology, Big Dog Ventures, Northrop Grumman Corporation, Mohr Davidow Ventures, and Applanix Inc.Attached Files
Accepted Version - DuToit2008p8756Ivcs_2008_Proceedings_Of_The_2Nd_International_Workshop_On_Intelligent_Vehicle_Control_Systems.pdf
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Additional details
- Eprint ID
- 19088
- Resolver ID
- CaltechAUTHORS:20100715-135111003
- Defense Advanced Research Projects Agency (DARPA)
- HR0011-06-C-0146
- Caltech
- Big Dog Ventures
- Northrop Grumman Corporation
- Mohr Davidow Ventures
- Applanix Inc.
- Created
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2010-08-04Created from EPrint's datestamp field
- Updated
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2019-10-03Created from EPrint's last_modified field