Autonomous mobile robots localization in large indoor environments by using ultrasound range sensors

doctoral thesis

• Title (croatian): Lokalizacija autonomnih mobilnih robota u velikim unutarnjim prostorima primjenom ultrazvučnih senzora udaljenosti
• Author: Lejla Banjanović-Mehmedović; strani drzavljanin: Nije dostupno
• Mentor: Ivan Petrović (mentor)
• Committee member: Nedjeljko Perić (član povjerenstva)
• Committee member: Ivan Petrović (član povjerenstva)
• Committee member: Naser Prljača (član povjerenstva); strani drzavljanin: Nije dostupno
• Committee member: Darko Žubrinić (član povjerenstva)
• Committee member: Željko Hocenski (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; (Department of Control and Computer Engineering); Zagreb
• Defense date and country: 2006-01-27, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Electrical Engineering; Automation and Robotics
• Universal decimal classification (UDC): 621.3 - Electrical engineering

Abstract

Global localization is the problem of determining the pose of a mobile robot under global uncertainty. The novel algorithm introduced here is based on the modified Multiple Modul (MM) Estimator and exploits a soft gating of the measurements (SGM) to reduce the computational requirements of presented approach. The localization approach uses a hybrid representation of the robot environment, topological with elements of metric.
This localization algorithm consists of a position estimation and orientation estimation part. The position part is based on a x and y histogram scan matching procedure, where x and y histograms are extracted directly from local occupancy grid maps, using Probability Scalar Transform (PST). Histograms obtained at the actual mobile robot pose are compared to nodes histograms with activity status from gated volume to compute position correction. The orientation part is based on two proposed methods: Obstacle Vector Transform (OVT) combined with Polar Histograms and Hough Transform (HT) combined with a non-iterative algorithm for determination of end points and length of straight-line parts combined with Angle Histograms. Histograms obtained at the actual mobile robot pose are compared to histograms saved at previous mobile robot poses to compute orientation correction. The proposed methods for mobile robot orientation correction are compared and present a worth alternative to the use of magnetic compass, particularly in environments with magnetic noise.
Sensors used for local occupancy grid generation are sonars but other exteroceptive sensors like a laser range finder can also be used. Experimental results with mobile robot Pioneer 2DX simulator and real robot show the capacity of this method.

Abstract (bosnian)

Globalna lokalizacija je problem odredjenja poze mobilnog robota uz prisustvo globalne neizvjesnosti. Novi algoritam predložen u radu je baziran na modifikovanom multi-modul (MM) estimatoru i koristi svojstva posebno definisanih mjerenja u cilju reduciranja računarske zahtjevnosti predloženog algoritma. Ovaj način lokalizacije koristi hibridnu reperezentaciju robotskog okruženja, topološki pristup sa elementima metrike.
Lokalizacioni algoritam sadrži dva dijela: pozicionu i orjentacionu estimaciju. Poziciona estimacija je zasnovana na usporedbi skanova, baziranih na x i y histogramima, gdje su x i y histogrami dobiveni direktno iz mrežne karte lokalne zauzetosti, korištenjem Vjerovatnosne Skalarne Transformacije (VST). Histogrami dobiveni na aktuelnoj pozi mobilnog robota se porede sa histogramima čvorova, čiji aktivni status je dobiven na osnovu vjerovatnosnog algoritma, čime se određuje poziciona korekcija. Orjentaciona estimacija je bazirana na dvije predložene metode: Transformacija Vektora Prepreke (PVT) kombinovana sa polarnim histogramom i Hougova Transformacija (HT) kombinovana sa ne-iterativnim algoritmom za određenje krajnjih točaka i dužine linijskog segmenta kombinovana sa ugaonim histogramima. Histogrami dobiveni na aktuelnoj pozi mobilnog robota su upoređeni sa histogramima sa predhodne poze mobilnog robota u cilju proračuna korekcije orjentacije. Predloženi metodi korekcije orijentacije mobilnog robota su međusobno upoređeni i predstavljaju vrijednu alternativu korištenju magnetnog kompasa, osobito u okruženjima sa magnetnim šumom.
Za generisanje lokalne karte zauzetosti korišteni su sonari senzori, ali i drugi opažajni senzori poput lasera mogu biti korišteni u tu svrhu. Eksperimentalni rezultati sa mobilnim robotskim simulatorom i realnim robotom Pioneer 2DX pokazuju kapacitet ove metode.

• Keywords: Mobile robot localization; histogram based scans matching; Probability Scalar Transform; Obstacle Vector Transform; Hough Transform; Multiple-hypothesis Tracking; soft gating; modify Multiple Modul (MM) Estimator
• Keywords (bosnian): Lokalizacija mobilnog robota; usporedba histogramski baziranih skanova; Vjerovatnosna Skalarna Transformacija; Transformacija Vektora Prepreke; Hougova Transformacija; praćenje više hipoteza; područje definisanog mjerenja; modifikovani multi-modul (MM) estimator
• Language: english
• URN:NBN: urn:nbn:hr:168:542275
• Study programme: Title: Doctoral study programme "Electrical Engineering and Computing"; Study programme type: university; Study level: postgraduate; Academic / professional title: doktor/doktorica znanosti, po-dručje tehničkih znanosti (doktor/doktorica znanosti, po-dručje tehničkih znanosti)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2019-07-16 13:02:33