Vision-based Wheel Sinkage Estimation for Rough-Terrain Mobile Robots (Contributo in atti di convegno)

Type

• Prodotto della ricerca (Classe)
• Contributo in atti di convegno (Classe)

Label

• Vision-based Wheel Sinkage Estimation for Rough-Terrain Mobile Robots (Contributo in atti di convegno) (literal)

Anno

• 2008-01-01T00:00:00+01:00 (literal)

Alternative label

• Giulio Reina, Annalisa Milella, Francesco Panella (2008)
  Vision-based Wheel Sinkage Estimation for Rough-Terrain Mobile Robots
  in 15th International Conference on Mechatronics and Machine Vision in Practice, Auckland, New Zealand
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Giulio Reina, Annalisa Milella, Francesco Panella (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto

• For mobile robots driving across soft soils, such as sand, loose dirt, or snow, it is critical that the dynamic effects occurring at the wheel-terrain interface be taken into account. One of the most prevalent of these effects is wheel sinkage. Wheels can sink in soft soils to depths sufficient to prohibit further motion, leading to danger of entrapment with consequent mission failure. This paper presents an algorithm for visual estimation of wheel sinkage in deformable terrain. We call it the Visual Sinkage Estimation (VSE) method. It assumes the presence of a monocular camera mounted on the wheel assembly, with a field of view containing the wheel–terrain interface. An artificial pattern, composed of concentric circumferences equally spaced apart on a white background, is attached to the wheel side in order to determine the contact angle with the terrain, following an edge detection strategy. The paper also introduces an analytical model for wheel sinkage in soft, deformable terrain based on terramechanics. In order to validate the VSE module, several tests were, first, performed on a single-wheel test bed, under different operating conditions including non-flat terrains, variable lighting conditions, and terrain with and without rocks. Successively, the effectiveness of the proposed approach in real context was proved, employing an all-terrain rover traveling on a sandy beach. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Università del Salento ISSIA CNR (literal)

Titolo

• Vision-based Wheel Sinkage Estimation for Rough-Terrain Mobile Robots (literal)

Prodotto di

• Sistemi Intelligenti per la sicurezza (SP.P06.004.001) (Modulo)
• Institute of intelligent systems for automation (ISSIA) (Istituto)

Autore CNR

• ANNALISA MILELLA (Unità di personale esterno)

Incoming links:

Prodotto

• Institute of intelligent systems for automation (ISSIA) (Istituto)
• Sistemi Intelligenti per la sicurezza (SP.P06.004.001) (Modulo)

Autore CNR di

• ANNALISA MILELLA (Unità di personale esterno)