Tracking a Mobile Robot Position Using Vision and Inertial Sensor - Technological Innovation for Collective Awareness Systems (DoCEIS 2014) Access content directly
Book Sections Year : 2014

Tracking a Mobile Robot Position Using Vision and Inertial Sensor

Francisco Coito
  • Function : Author
  • PersonId : 976765
António Eleutério
  • Function : Author
  • PersonId : 976766
Stanimir Valtchev
  • Function : Author
  • PersonId : 976767
Fernando Coito
  • Function : Author
  • PersonId : 976768

Abstract

Wheeled mobile robots are still the first choice when it comes to industrial or domotic applications. The robot’s navigation system aims to reliably determine the robot’s position, velocity and orientation and provide it to control and trajectory guidance modules. The most frequently used sensors are inertial measurement units (IMU) combined with an absolute position sensing mechanism. The dead reckoning approach using IMU suffers from integration drift due to noise and bias. To overcome this limitation we propose the use of the inertial system in combination with mechanical odometers and a vision based system. These two sensor complement each other as the vision sensor is accurate at low-velocities but requires long computation time, while the inertial sensor is able to track fast movements but suffers from drift. The information from the sensors is integrated through a multi-rate fusion scheme. Each of the sensor systems is assumed to have it’s own independent sampling rate, which may be time-varying. Data fusion is performed by a multi-rate Kalman filter. The paper describes the inertial and vision navigation systems, and the data fusion algorithm. Simulation and experimental results are presented.
Fichier principal
Vignette du fichier
978-3-642-54734-8_23_Chapter.pdf (4 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01274775 , version 1 (16-02-2016)

Licence

Attribution - CC BY 4.0

Identifiers

Cite

Francisco Coito, António Eleutério, Stanimir Valtchev, Fernando Coito. Tracking a Mobile Robot Position Using Vision and Inertial Sensor. Luis M. Camarinha-Matos; Nuno S. Barrento; Ricardo Mendonça. Technological Innovation for Collective Awareness Systems : 5th IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2014, Costa de Caparica, Portugal, April 7-9, 2014. Proceedings, AICT-423, Springer, pp.201-208, 2014, IFIP Advances in Information and Communication Technology, 978-3-642-54733-1. ⟨10.1007/978-3-642-54734-8_23⟩. ⟨hal-01274775⟩
76 View
602 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More