Precizna detekcija prometnih čunjeva laserskim senzorom udaljenosti na stazama za utrku automobila

undergraduate thesis

• Title (english): Accurate traffic cone detection in racing environments based on a LIDAR sensor
• Author: Ante Vinković
• Mentor: Ivan Marković (mentor)
• Committee member: Ivan Marković (član povjerenstva)
• Committee member: Goran Popović (član povjerenstva)
• Committee member: Ivan Bilić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2022-09-01, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Detekcija i lokalizacija značajki u prostoru ima važnu ulogu u autonomiji vozila jer je to preduvjet za ispravno zaključivanje o okolini vozila. Okoline koje su ljudi napravili često imaju lako uočljive diskretne markere za olakšanu estimaciju položaja autonomnih sustavima. Studentsko natjecanje "Formula Student Driverless" (FSD) primjer je takve okoline gdje prometni čunjevi označavaju rubove staze. U tom natjecanju FSD trkaći bolid treba autonomno doći do cilja. Zbog zahtjeva za točnošću laserski senzor udaljenosti se koristi za određivanje udaljenosti između trkaćeg bolida i čunjeva. U ovom radu istraženo je kako iz oblaka točaka snimljenih laserskim senzorom udaljenosti izdvojiti čunjeve uzimajući u obzir poznatu strukturu trkaće staze.

Abstract (english)

Feature detection and localization play an important role in vehicle autonomy because it is a prerequisite for correct inference about the vehicle's environment. Man-made environments often contain fiducial distinctive markers which autonomous systems use to determine their position. The "Formula Student Driverless" (FSD) competition is an example of such an environment, containing traffic cones as markers used to determine the track edges. In the competition, a FSD race car needs to autonomously reach the finish line. Due to accuracy requirements, a light detection and ranging sensor is used to detect traffic cones and determine their position relative to the race car. This thesis investigates and applies traffic cone extraction from point cloud data, considering the racing environment structure.

• Keywords: lidar; pointcloud; uklanjanje tla; segmentacija tla; RANSAC; autonomna vožnja; grupiranje; formula student; driverless; FS; FSD
• Keywords (english): lidar; point cloud; ground removal; ground segmentation; RANSAC; autonomous driving; clustering; formula student; driverless; FS; FSD
• Language: english
• URN:NBN: urn:nbn:hr:168:710547
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-15 11:24:50