Robust mobile robot localisation from sparse and noisy proximity readings using Hough transform and probability grids

Robotics and Autonomous Systems

Volumn 37, Issue 1, 2001, Pages 1-18

  Großmann, Axel ^b   Poli, Riccardo ^a  

^a UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^b DRESDEN UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

Hough transform; Markov localisation; Position tracking method; Probability grids; Sonar sensors

Indexed keywords

FEATURE EXTRACTION; HOUGH TRANSFORMS; MARKOV PROCESSES; NAVIGATION SYSTEMS; REFLECTION; SENSORS; SONAR; TRACKING (POSITION);

PROBABILITY GRIDS; SONAR SENSORS;

MOBILE ROBOTS;

EID: 4444289059     PISSN: 09218890     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0921-8890(01)00144-0     Document Type: Article

References (18)

1. Integrating behavioural, perceptual, and world knowledge in reactive navigation
2. Generalising the Hough transform to detect arbitrary shapes
3. Active mobile robot localisation
4. Fast grid-based position tracking for mobile robots
5. Active mobile robot localisation by entropy minimisation
6. World modeling and position estimation for a mobile robot using ultrasonic ranging
7. Mobile robot localisation using sonar
8. Continual robot learning with constructive neural networks
9. An experimental comparison of localisation methods
10. A new approach to linear filtering and prediction problems
11. Markov localisation using correlation
12. Hough space transformations for discrimination and distortion estimation
13. Discretisation errors in the Hough transform
14. Mobile robot localisation using the Hough transform and neural networks