@misc{Werner2024,
  type      = {Master Thesis},
  author    = {Werner, Lennart},
  title     = {Terrain Mapping for Autonomous Navigation of Lunar Rovers},
  doi       = {10.25972/OPUS-35826},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-358268},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2024},
  abstract  = {Autonomous mobile robots operating in unknown terrain have to guide their drive decisions through local perception. Local mapping and traversability analysis is essential for safe rover operation and low level locomotion. This thesis deals with the challenge of building a local, robot centric map from ultra short baseline stereo imagery for height and traversability estimation. Several grid-based, incremental mapping algorithms are compared and evaluated in a multi size, multi resolution framework. A new, covariance based mapping update is introduced, which is capable of detecting sub- cellsize obstacles and abstracts the terrain of one cell as a first order surface. The presented mapping setup is capable of producing reliable ter- rain and traversability estimates under the conditions expected for the Cooperative Autonomous Distributed Robotic Exploreration (CADRE) mission. Algorithmic- and software architecture design targets high reliability and efficiency for meeting the tight constraints implied by CADRE's small on-board embedded CPU. Extensive evaluations are conducted to find possible edge-case scenar- ios in the operating envelope of the map and to confirm performance parameters. The research in this thesis targets the CADRE mission, but is applicable to any form of mobile robotics which require height- and traversability mapping.},
  subject      = {Mondfahrzeug},
  language  = {en}
}