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Autonomous Stair Climbing for Tracked Vehicles

University of Minnesota Department of Computer Science and Engineering Minneapolis, MN, @cs.umn.edu

Nikolas Trawny

University of Minnesota Department of Computer Science and Engineering Minneapolis, MN, @cs.umn.edu

Stergios I. Roumeliotis

University of Minnesota Department of Computer Science and Engineering Minneapolis, MN, @cs.umn.edu

Daniel M. Helmick

Jet Propulsion Laboratory California Institute of Technology Pasadena, CA, dhelmick{at}robotics.jpl.nasa.gov

Larry Matthies

Jet Propulsion Laboratory California Institute of Technology Pasadena, CA, lhm{at}telerobotics.jpl.nasa.gov

In this paper, an algorithm for autonomous stair climbing with a tracked vehicle is presented. The proposed method achieves robust performance under real-world conditions, without assuming prior knowledge of the stair geometry, the dynamics of the vehicle's interaction with the stair surface, or lighting conditions. The approach relies on fast and accurate estimation of the robot's heading and its position relative to the stair boundaries. An extended Kalman filter is used for quaternion-based attitude estimation, fusing rotational velocity measurements from a 3-axial gyroscope, and measurements of the stair edges acquired with an onboard camera. A two-tiered controller, comprised of a centering- and a heading-control module, utilizes the estimates to guide the robot rapidly, safely, and accurately upstairs. Both the theoretical analysis and implementation of the algorithm are presented in detail, and extensive experimental results demonstrating the algorithm's performance are described.

Key Words: stair climbing • autonomous robots • inertial sensing • attitude estimation • computer vision.

The International Journal of Robotics Research, Vol. 26, No. 7, 737-758 (2007)
DOI: 10.1177/0278364907080423


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