Pose estimation is one of the vital issues in mobile robot navigation. Odometry data can be fused with absolute position measurements to provide better and more reliable pose estimation. This paper deals with the determination of better relative localization of a two wheeled differential drive robot by means of odometry by considering the influence of parameters namely weight, velocity, wheel p...

Purpose – This paper aims to provide a simple and cheap calibration method to improve the odometry accuracy and to present an alternative method for the control of the path produced by an already existed path planning method. Design/methodology/approach – Through the integration of systematic odometry errors the robot’s odometry parameters are estimated and through the replacement of a caster w...

Odometry is an important input to robot navigation systems, and we are interested in the performance of vision-only techniques. In this paper we experimentally evaluate and compare the performance of wheel odometry, monocular feature-based visual odometry, monocular patch-based visual odometry, and a technique that fuses wheel odometry and visual odometry, on a mobile robot operating in a typic...

Abstract: This paper proposes a method for combining stereo visual odometry, Light Detection And Ranging (LiDAR) odometry and reduced Inertial Measurement Unit (IMU) including two horizontal accelerometers and one vertical gyro. The proposed method starts with stereo visual odometry to estimate six Degree of Freedom (DoF) ego motion to register the point clouds from previous epoch to the curren...

The improvement of odometry systems in collaborative robotics remains an important challenge for several applications. Social odometry is a social technique which confers the robots the possibility to learn from the others. This paper analyzes social odometry and proposes and follows a methodology to improve its behavior based on cooperative reputation systems. We also provide a reference imple...

It is often the odometry accumulative error without bound after long-range movement that decreases the precision of global localization for wheeled mobile robots. Therefore, an efficient approach to odometry error modeling is proposed regarding gentle drive type mobile robots. The approximate functional expressions, between process input of odometry and non-systematic error as well as systemati...

This article describes the theoretical and implementation challenges associated with generating 3D odometry estimates (delta-pose) from RGBD sensor data in real-time to facilitate navigation in cluttered indoor environments. The underlying odometry algorithm applies to general 6DoF motion; however, the computational platforms, trajectories, and scene content are motivated by their intended use ...

We present an unsupervised deep neural network approach to the fusion of RGB-D imagery with inertial measurements for absolute trajectory estimation. Our network, dubbed the Visual-Inertial-Odometry Learner (VIOLearner), learns to perform visual-inertial odometry (VIO) without inertial measurement unit (IMU) intrinsic parameters (corresponding to gyroscope and accelerometer bias or white noise)...