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dc.contributor.advisorJohn Leonarden_US
dc.contributor.authorLeonard, Johnen_US
dc.contributor.authorBarrett, Daviden_US
dc.contributor.authorHow, Jonathanen_US
dc.contributor.authorTeller, Sethen_US
dc.contributor.authorAntone, Matten_US
dc.contributor.authorCampbell, Stefanen_US
dc.contributor.authorEpstein, Alexen_US
dc.contributor.authorFiore, Gastonen_US
dc.contributor.authorFletcher, Lukeen_US
dc.contributor.authorFrazzoli, Emilioen_US
dc.contributor.authorHuang, Alberten_US
dc.contributor.authorJones, Troyen_US
dc.contributor.authorKoch, Olivieren_US
dc.contributor.authorKuwata, Yoshiakien_US
dc.contributor.authorMahelona, Keonien_US
dc.contributor.authorMoore, Daviden_US
dc.contributor.authorMoyer, Katyen_US
dc.contributor.authorOlson, Edwinen_US
dc.contributor.authorPeters, Stevenen_US
dc.contributor.authorSanders, Chrisen_US
dc.contributor.authorTeo, Justinen_US
dc.contributor.authorWalter, Matthewen_US
dc.contributor.otherRobotics, Vision & Sensor Networksen_US
dc.date.accessioned2007-12-17T13:50:57Z
dc.date.available2007-12-17T13:50:57Z
dc.date.issued2007-12-14en_US
dc.identifier.otherMIT-CSAIL-TR-2007-058en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/39822
dc.description.abstractThis technical report describes Team MIT’s approach to theDARPA Urban Challenge. We have developed a novel strategy forusing many inexpensive sensors, mounted on the vehicle periphery,and calibrated with a new cross-­modal calibrationtechnique. Lidar, camera, and radar data streams are processedusing an innovative, locally smooth state representation thatprovides robust perception for real­ time autonomous control. Aresilient planning and control architecture has been developedfor driving in traffic, comprised of an innovative combination ofwell­proven algorithms for mission planning, situationalplanning, situational interpretation, and trajectory control. These innovations are being incorporated in two new roboticvehicles equipped for autonomous driving in urban environments,with extensive testing on a DARPA site visit course. Experimentalresults demonstrate all basic navigation and some basic trafficbehaviors, including unoccupied autonomous driving, lanefollowing using pure-­pursuit control and our local frameperception strategy, obstacle avoidance using kino-­dynamic RRTpath planning, U-­turns, and precedence evaluation amongst othercars at intersections using our situational interpreter. We areworking to extend these approaches to advanced navigation andtraffic scenarios.en_US
dc.format.extent26 p.en_US
dc.relationMassachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratoryen_US
dc.relationen_US
dc.subjectautonomous vehicleen_US
dc.subjectroboticsen_US
dc.subjectDARPA Grand Challengeen_US
dc.subjectpath planningen_US
dc.subjectmachine perceptionen_US
dc.subjecttrackingen_US
dc.titleTeam MIT Urban Challenge Technical Reporten_US


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