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Autonomous Driving in Urban Environments: Boss and the Urban Challenge
TLDR
This dissertation aims to provide a history of web exceptionalism from 1989 to 2002, a period chosen in order to explore its roots as well as specific cases up to and including the year in which descriptions of “Web 2.0” began to circulate.
Autonomous driving in urban environments: Boss and the Urban Challenge
TLDR
Boss is an autonomous vehicle that uses on‐board sensors to track other vehicles, detect static obstacles, and localize itself relative to a road model using a spiral system development process with a heavy emphasis on regular, regressive system testing.
Autonomous driving in urban environments: Boss and the Urban Challenge
TLDR
Boss is an autonomous vehicle that uses on-board sensors to track other vehicles, detect static obstacles, and localize itself relative to a road model using a spiral system development process with a heavy emphasis on regular, regressive system testing.
Detection, prediction, and avoidance of dynamic obstacles in urban environments
TLDR
After detecting a dynamic obstacle, the approach exploits structure in the environment where possible to generate a set of likely hypotheses for the future behavior of the obstacle and efficiently incorporates these hypotheses into the planning process to produce safe actions.
The SmartTer for ELROB 2006 - a Vehicle for Fully Autonomous Navigation and Mapping in Outdoor Environments
The goal of our participation ELROB 2006 is to show fully autonomous navigation and 3D mapping in outdoor setting. Our robots is based on a standard Smart car that has been equipped with five
Autonomous Driving in Structured and Unstructured Environments
TLDR
This paper presents a hybrid autonomous system that recognizes and exploits structure in the environment in the form of driving lanes, yet also navigates successfully when no such information is present, believed to be more flexible and more robust than either of its sub-components alone.
Calibration of an embedded camera for driver-assistant systems
TLDR
The two-step calibration procedure presented here has been designed to simplify the calibration of the mounted cameras in the truck production line to precisely determine the position of obstacles situated in a 100 meter range.
Mobile Robot Planning in Dynamic Environments and on Growable Costmaps
TLDR
A relatively general purpose system and a limited amount of well-defined user-definable heuristics that allow users to adapt the system to a given application are introduced.
Autonomous driving in dynamic environments
TLDR
The algorithms presented in this thesis where widely tested on the SmartTer vehicle at EPFL and ETH and during the preparation of the DARPA Urban Challenge entry of the Tartanracing Team at Carnegie Mellon University in Pittsburgh, Pennsylvania, USA.
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