Collaborative SLAM for outdoor environments

Abstract : This thesis proposes large-scale mapping model of urban and rural environments using 3D data acquired by several robots. The work contributes in two main ways to the research field of mapping. The first contribution is the creation of a new framework, CoMapping, which allows to generate 3D maps in a cooperative way. This framework applies to outdoor environments with a decentralized approach. The CoMapping's functionality includes the following elements: First of all, each robot builds a map of its environment in point cloud format.To do this, the mapping system was set up on computers dedicated to each vehicle, processing distance measurements from a 3D LiDAR moving in six degrees of freedom (6-DOF). Then, the robots share their local maps and merge the point clouds individually to improve their local map estimation. The second key contribution is the group of metrics that allow to analyze the merging and card sharing processes between robots. We present experimental results to validate the CoMapping framework with their respective metrics. All tests were carried out in urban outdoor environments on the surrounding campus of the École Centrale de Nantes as well as in rural areas.
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Luis Federico Contreras Samamé. Collaborative SLAM for outdoor environments. Automatic. École centrale de Nantes, 2019. English. ⟨NNT : 2019ECDN0012⟩. ⟨tel-02421236⟩

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