Hardware implementation of ground classification for a walking robot
Krzysztof Walas, Adam Schmidt, Marek Kraft, Michał Fularz
- Year
- 2013
- Citations
- 4
Abstract
The mobile robot requires the knowledge about the ground type in front of it to efficiently negotiate diverse terrain types while working outdoors. This article presents the implementation of ground classification algorithms in a Field Programmable Gate Array structure. The terrain type classification is based on the signals acquired with force/torque sensor mounted on the walking robot foot. The hardware implementation allows for offloading of the resource demanding computations. The paper begins with a short presentation of the experimental setup. Then the classification algorithms are described. Finally the description of hardware implementation of the algorithms is given followed by the test results.
Keywords
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002