Abstract
Small, tracked mobile robots designed for general urban mobility have been developed for the purpose of reconnaissance and/or search and rescue missions in buildings and cities. Autonomous stair climbing is a significant capability required for many of these missions. In this paper we present the design and implementation of a new set of estimation and control algorithms that increase the speed and effectiveness of stair climbing. We have developed: (i) a Kalman filter that fuses visual/laser data with inertial measurements and provides attitude estimates of improved accuracy at a high rate, and (ii) a physics based controller that minimizes the heading error and maximizes the effective velocity of the vehicle during stair climbing. Experimental results using a tracked vehicle validate the improved performance of this control and estimation scheme over previous approaches.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE International Conference on Intelligent Robots and Systems |
| Pages | 733-742 |
| Number of pages | 10 |
| Volume | 1 |
| State | Published - Jan 1 2002 |
| Event | 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems - Lausanne, Switzerland Duration: Sep 30 2002 → Oct 4 2002 |
Other
| Other | 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems |
|---|---|
| Country/Territory | Switzerland |
| City | Lausanne |
| Period | 9/30/02 → 10/4/02 |
