Odometry | EPFL Graph Search

Odometry is the use of data from motion sensors to estimate change in position over time. It is used in robotics by some legged or wheeled robots to estimate their position relative to a starting location. This method is sensitive to errors due to the integration of velocity measurements over time to give position estimates. Rapid and accurate data collection, instrument calibration, and processing are required in most cases for odometry to be used effectively. The word odometry is composed of the Greek words odos (meaning "route") and metron (meaning "measure"). Example Suppose a robot has rotary encoders on its wheels or on its legged joints. It drives forward for some time and then would like to know how far it has traveled. It can measure how far the wheels have rotated, and if it knows the circumference of its wheels, compute the distance. Train operations are also frequent users of odometrics. Typically, a train gets an absolute position by passing over stationary

Robot Identification and Localization with Pointing Gestures

We propose a novel approach to establish the relative pose of a mobile robot with respect to an operator that wants to interact with it; we focus on scenarios in which the robot is in the same environment as the operator, and is visible to them. The approach is based on comparing the trajectory of the robot, which is known in the robot's odometry frame, to the motion of the arm of the operator, who, for a short time, keeps pointing at the robot they want to interact with. In multi-robot scenarios, the same approach can be used to simultaneously identify which robot the operator wants to interact with. The main advantage over alternatives is that our system only relies on the robot's odometry, on a wearable inertial measurement unit (IMU), and, crucially, on the operator's own perception. We experimentally show the feasibility of our approach using real-world robots.

2019

3D Position Tracking in Challenging Terrain

Pierre Lamon, Roland Siegwart

The intent of this paper is to show how the accuracy of 3D position tracking can be improved by considering rover locomotion in rough terrain as a holistic problem. An appropriate locomotion concept endowed with a controller min- imizing slip improves the climbing performance, the accuracy of odometry and the signal/noise ratio of the onboard sensors. Sensor fusion involving an inertial mea- surement unit, 3D-Odometry, and visual motion estimation is presented. The exper- imental results show clearly how each sensor contributes to increase the accuracy of the 3D pose estimation in rough terrain.

2005

Theoretical Results on On-line Sensor Self-Calibration

Roland Siegwart, Jan Weingarten

In this paper we derive theoretical results for the problem of on-line sensor calibration for a mobile robot. We consider the case of the odometry sensor. A first series of results regards the problem of understanding if a given system (consisting of a robot with several sensors) contains the necessary information to perform the on-line self calibration of one of its sensors. We consider several cases corresponding to different odometry systems and different types of robot sensors. Finally, we also consider the problem of maximizing the calibration accuracy and we formulate this problem as an optimal control problem. For the special case of a holonomic vehicle, we derive an analytical solution, i.e. we find the best trajectory which maximizes the calibration accuracy.

2006