Estimating the Odometry Error of a Mobile Robot during Navigation
Related publications (68)
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
This thesis presents a recent research on the problem of environmental modeling for both localization and map building for wheel-based, differential driven, fully autonomous and self-contained mobile robots. The robots behave in an indoor office environmen ...
This paper discusses mobile robot localization by means of geometric features from a laser range finder and a CCD camera. The features are line segments from the laser scanner and vertical edges from the camera. Emphasis is put on sensor models with a stro ...
In this paper a multisensor setup for localization consisting of a 360 degree laser range finder and a monocular vision system is presented. Its practicability under conditions of continuous localization during motion in real-time (referred to as on-the-fl ...
This paper focuses on issues of odometry for the special case of synchronous drive wheeled mobile robots. In particular, the uncertainty in odometry is modeled by a four parameter statistical model already introduced in previous works together with a strat ...
This paper presents both an error modeling of an odometry system and a possible procedure in order to evaluate this error. This error contains systematic and non-systematic components. In this paper both components have been evaluated for the mobile robot ...
This paper presents an error modeling of an odometry system for a synchronous-drive system and a possible strategy for evaluating this error. The odometry error is modeled by introducing four parameters characterizing its systematic and nonsystematic compo ...
The Autonomous Systems Lab at the Swiss Federal Institute of Technology Lausanne (EPFL) is engaged in mobile robotics research. The labs research focuses mainly on indoor localization and map building, outdoor locomotion and navigation, and micro mobile r ...
In this paper a new localization approach combining the metric and topological paradigm is presented. The main idea is to connect local metric maps by means of a global topological map. This allows a compact environment model which does not require global ...