Ground Disturbance Rejection Approach for Mobile Robotic Manipulators with Hydraulic Actuators
Mattia Rigotti-Thompson, Miguel Torres‐Torriti, Fernando Auat Cheein, Giancarlo Troni
- 发表年份
- 2018
- 引用次数
- 4
摘要
Reducing material spillage by robotic mining mobile manipulators, such as front-end loaders, is necessary to improve mining operations. To this end, the present work proposes an approach to reduce disturbances on the end-effector induced by the terrain and propagated through the wheels and arm links of the machine. The proposed approach is based on an H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control strategy that includes a feedforward action, computed using the pitch rate of the mobile base, and considers the hydraulic arm dynamics, as well as the reaction forces in the contact points of the mobile base, which is modeled as a floating body with non-permanent ground contacts. Alternative control schemes based on the classic proportional-derivative (PD) control, and the Active Disturbance Rejection Control (ADRC), with and without feedforward action, were also implemented and experimentally evaluated using a semiautonomous Cat <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">®</sup> 262C compact skid-steer loader equipped with inclination and inertial sensors. The proposed method reduces disturbances by at least 70% when climbing ramps at 25% of the machine's maximum speed, and by at least 20% when driving over speed bumps which produce disturbances similar to that caused by stones. The proposed disturbance attenuation strategy should help reducing the spillage of material when driving over mounds, inclines or spilled rocks, especially considering that even if existing autonomous machines are able to drive with little operator supervision along mining galleries, they are often unable to avoid disturbing material on the ground or the characteristic unevenness of mining terrains.
关键词
相关论文
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