odometry
In plain wordsEstimating how far and in which direction a robot or vehicle has moved by adding up its own motion, such as wheel turns or how camera images shift, like counting your steps.
Estimation of how far, and in what direction, a robot or vehicle has moved and turned, obtained by accumulating measurements of its own motion. Wheel odometry counts wheel rotations with encoders; visual odometry tracks how features or pixels move between successive camera frames; lidar odometry aligns consecutive scans; inertial odometry integrates accelerometer and gyroscope readings from an inertial measurement unit; and visual-inertial odometry fuses camera and inertial data, as in phones, drones and VR headsets. Because each step's small error carries into the next, odometry drifts without bound — wheel slip, uneven floors and sensor bias make the estimate wander over long distances — so it is usually combined through sensor fusionsensor fusion, n.: Combining readings from several different sensors, such as cameras, radar, lidar, GPS and motion sensors, to get a more accurate and reliable picture than any one sensor gives alone. with absolute references such as GPS, known landmarks or the loop closures of simultaneous localization and mappingsimultaneous localization and mapping, n.: How a robot, drone or headset builds a map of an unfamiliar place while at the same time working out where it is on that map, using its cameras or laser scanners.. It is nonetheless the backbone of short-term motion estimation in nearly every mobile robotmobile robot, n.: A robot that travels around by itself — on wheels, tracks, legs, propellers or thrusters — such as a robot vacuum, warehouse cart, delivery robot or planetary rover..
Visual odometry kept the drone's position within a few centimeters until GPS came back.
Origin
From Greek hodos, 'way' or 'route', and metron, 'measure'; wheel-counting odometers date to antiquity. 'Visual odometry' was introduced by David Nistér, Oleg Naroditsky and James Bergen in a 2004 CVPR paper, building on camera-based motion estimation for robots by Larry Matthies and others since the 1980s; NASA's Mars Exploration Rovers used visual odometry from 2004.
Related
- simultaneous localization and mappingsimultaneous localization and mapping, n.: How a robot, drone or headset builds a map of an unfamiliar place while at the same time working out where it is on that map, using its cameras or laser scanners.
- sensor fusionsensor fusion, n.: Combining readings from several different sensors, such as cameras, radar, lidar, GPS and motion sensors, to get a more accurate and reliable picture than any one sensor gives alone.
- Kalman filterKalman filter, n.: A method that keeps a running best guess of something you cannot measure exactly, such as a vehicle's position, by blending predictions from a motion model with noisy sensor readings.
- mobile robotmobile robot, n.: A robot that travels around by itself — on wheels, tracks, legs, propellers or thrusters — such as a robot vacuum, warehouse cart, delivery robot or planetary rover.
- optical flowoptical flow, n.: How each part of a video picture seems to shift from one frame to the next, recorded as a tiny arrow per pixel giving the direction and distance moved.
- proprioceptionproprioception, n.: A robot's sense of its own body: where its joints are, how fast they are moving and how hard its motors are pushing, measured by internal sensors rather than cameras.
Sources
- Nistér, D., Naroditsky, O. & Bergen, J. (2004). Visual odometry. Proc. IEEE CVPR 2004.
- Scaramuzza, D. & Fraundorfer, F. (2011). Visual odometry: Part I. IEEE Robotics & Automation Magazine 18(4), 80–92.
Mentioned in
dronedrone, n.: An aircraft that carries no one aboard to fly it: a person steers it from the ground, or its own software does. Small camera-carrying quadcopters are the most familiar kind., Kalman filterKalman filter, n.: A method that keeps a running best guess of something you cannot measure exactly, such as a vehicle's position, by blending predictions from a motion model with noisy sensor readings., keypoint detectionkeypoint detection, n.: Finding specific, recognizable points in an image, such as the corners of a building, a person's elbows and knees, or the tip of a nose., lidarlidar, n.: A sensor that measures distances by firing laser pulses and timing their reflections, building a 3D picture of its surroundings out of millions of points; widely used on robots and self-driving cars., mobile robotmobile robot, n.: A robot that travels around by itself — on wheels, tracks, legs, propellers or thrusters — such as a robot vacuum, warehouse cart, delivery robot or planetary rover., pose estimationpose estimation, n.: Working out the position and orientation of something from images: where a person's joints are and how their body is posed, or exactly how an object or camera is placed and turned in space., sensor fusionsensor fusion, n.: Combining readings from several different sensors, such as cameras, radar, lidar, GPS and motion sensors, to get a more accurate and reliable picture than any one sensor gives alone., simultaneous localization and mappingsimultaneous localization and mapping, n.: How a robot, drone or headset builds a map of an unfamiliar place while at the same time working out where it is on that map, using its cameras or laser scanners., optical flowoptical flow, n.: How each part of a video picture seems to shift from one frame to the next, recorded as a tiny arrow per pixel giving the direction and distance moved., proprioceptionproprioception, n.: A robot's sense of its own body: where its joints are, how fast they are moving and how hard its motors are pushing, measured by internal sensors rather than cameras.