Robust bucket position tracking for a large hydraulic excavator

The device we study is the excavation arm of a large hydraulic mining shovel having a multi-loop kinematic form. We describe an iterative algorithm that allows the position of the bucket to be tracked from measurements of the linear actuator extensions. The important characteristic of this algorithm is that it is numerically well-behaved when the linkage is close to singular configurations. While we focus on a specific device, the algorithm is easy to adapt to other multi-loop linkages. (C) 2004 Elsevier Ltd. All rights reserved.

Tuning pattern classifier parameters using a genetic algorithm with an application in mobile robotics

Support vector machines (SVMs) have recently emerged as a powerful technique for solving problems in pattern classification and regression. Best performance is obtained from the SVM its parameters have their values optimally set. In practice, good parameter settings are usually obtained by a lengthy process of trial and error. This paper describes the use of genetic algorithm to evolve these parameter settings for an application in mobile robotics.