LiDAR odometry plays an important role in self-localization and mapping for autonomous navigation, which is usually treated as a scan registration problem. Although having achieved promising performance on the KITTI benchmark, conventional tree-based neighbor search still has difficulty dealing with large-scale point cloud efficiently. The recent spherical range image-based method enjoys merits...

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We describe a visual odometry algorithm for estimating frame-to-frame camera motion from successive stereo image pairs. This algorithm differs from most visual odometry algorithms in two key respects: it makes no prior assumptions about camera motion, and (2) it operates on dense disparity images (computed by a separate stereo algorithm). As a consequence, the algorithm is robust in the presenc...

This paper presents a model-based odometry calculation and calibration method (MBO) for quadruped robots. Instead of establishing the direct relation between target and actual speeds as previous methods did, MBO sets up a “parametric physical model” incorporating various properties of the robot and environment such as friction and inertia, through optimization with locomotor data. Based on this...

Most simultaneous localisation and mapping (SLAM) solutions were developed for navigation of non-cognitive robots. By using a variety of sensors, the distances to walls and other objects are determined, which are then used to generate a map of the environment and to update the robot’s position. When developing a cognitive robot, such a solution is not appropriate since it requires accurate sens...

We are presenting a method for correcting odometry readings of a robot for increased accuracy of position estimation. Our method uses a simple pragmatic approach and exploits the distinct structure of the floor in our experimental area. By continually extracting orientation information from the floor view, we are able to correct the heading component of odometry, thereby eliminating the major s...

A wide variety of techniques for visual navigation using robot-mounted cameras have been described over the past several decades, yet adoption of optical flow navigation techniques has been slow. This demo illustrates what visual navigation has to offer: robust hazard detection (including precipices and obstacles), high-accuracy open-loop odometry, and stable closed-loop motion control implemen...

We present a solution for motion estimation for a set of cameras which are firmly mounted on a head unit and do not have overlapping views in each image. This problem relates to ego-motion estimation of multiple cameras, or visual odometry. We reduce motion estimation to solving a triangulation problem, which finds a point in space from multiple views. The optimal solution of the triangulation ...

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 minimizing slip improves the climbing performance, the accuracy of odometry and the signal/noise ratio of the onboard sensors. Sensor fusion involving an inertial measureme...