Vođenje hodajućeg robota u strukturiranom prostoru zasnovano na računalnome vidu

Locomotion of a biped robot in a scenario with obstacles requires a high degree of coordination between perception and walking. This article presents key ideas of a vision-based strategy for guidance of walking robots in structured scenarios. Computer vision techniques are employed for reactive adaptation of step sequences allowing a robot to step over or upon or walk around obstacles. Highly accurate feedback information is achieved by a combination of line-based scene analysis and real-time feature tracking. The proposed vision-based approach was evaluated by experiments with a real humanoid robot.Lokomocija dvonožnog robota u prostoru s preprekama zahtijeva visoki stupanj koordinacije između percepcije i hodanja. U članku se opisuju ključne postavke strategije vođenja hodajućih robota zasnovane na računalnome vidu. Tehnike računalnoga vida primijenjene za reaktivnu adaptaciju slijeda koraka omogućuju robotu zaobilaženje prepreka, ali i njihovo prekoračivanje te penjanje na njih. Visoka točnost povratne informacije postignuta je kombinacijom analize linijskih segmenata u sceni i praćenjem značajki scene u stvarnome vremenu. Predloženi je sustav vođenja hodajućih robota eksperimentalno provjeren na stvarnome čovjekolikome robotu

Registracija stereo slika postupkom zasnovanim na RANSAC strategiji s geometrijskim ograničenjem na generiranje hipoteza.

An approach for registration of sparse feature sets detected in two stereo image pairs taken from two different views is proposed. Analogously to many existing image registration approaches, our method consists of initial matching of features using local descriptors followed by a RANSAC-based procedure. The proposed approach is especially suitable for cases where there is a high percentage of false initial matches. The strategy proposed in this paper is to modify the hypothesis generation step of the basic RANSAC approach by performing a multiple-step procedure which uses geometric constraints in order to reduce the probability of false correspondences in generated hypotheses. The algorithm needs approximate information about the relative camera pose between the two views. However, the uncertainty of this information is allowed to be rather high. The presented technique is evaluated using both synthetic data and real data obtained by a stereo camera system.U radu je predložen jedan pristup registraciji skupova značajki detektiranih na dva para stereo slika snimljenih iz dva različita pogleda. Slično mnogim postojećim pristupima registraciji slika, predložena se metoda sastoji od početnog sparivanja značajki na temelju lokalnih deskriptora iza kojeg slijedi postupak temeljen na RANSAC-strategiji. Predloženi je pristup posebno prikladan za slučajeve kada rezultat početnog sparivanja sadrži veliki postotak pogrešno sparenih značajki. Strategija koja se predlaže u ovom članku je da se korak RANSAC-algoritma u kojem se slučajnim uzorkovanjem generiraju hipoteze zamijeni postupkom u kojem se hipoteza generira u više koraka, pri čemu se u svakom koraku, korištenjem odgovarajućih geometrijskih ograničenja, smanjuje vjerojatnost izbora pogrešno sparenih značajki. Algoritam treba približnu informaciju o relativnom položaju kamera između dva pogleda, pri čemu je dopuštena nesigurnost te informacije prilično velika. Predstavljena strategija je provjerena korištenjem sintetičkih podataka te pokusima sa slikama snimljenim pomoću stereo sustava kamera

Prikaz slobodnog prostora za dvonožne hodajuće robote

Motion planning for biped walking robots is a highly demanding task because of the complex kinematics of such machines and the many degrees of freedom involved. One approach to dealing with this problem is to determine a feasible path in a reduced configuration space of the robot and then to perform the motion planning by searching for an appropriate sequence of steps which allows the locomotion along this path. In this work, a novel method for creating a free space representation for biped walking robots is presented. The method rests upon the approximation of the robot by a set of 3D hulls whose shapes allow efficient determination of feasible paths in a 3D configuration space, involving stepping over obstacles and changing the walking level. The robot’s environment is partitioned into two regions. In the first region, 2D motion planning can be performed, while the complexity of 3D motion planning in the second region can be significantly reduced by considering only a restricted set of paths sufficient for solving a wide range of locomotion tasks.Planiranje kretanja dvonožnih hodajućih robota predstavlja iznimno zahtjevan zadatak zbog složenosti kinematike takvih strojeva i velikog broja stupnjeva slobode gibanja. Jedan pristup tom problemu je da se prvo pronađe izvediva staza u reduciranom konfiguracijskom prostoru robota te da se zatim traži odgovarajući niz koraka koji omogućuje kretanje tom stazom. U ovom radu predstavljena je nova metoda stvaranja prikaza slobodnog prostora za dvonožne hodajuće robote. Metoda se temelji na aproksimaciji robota skupom jednostavnih trodimenzionalnih geometrijskih tijela čiji oblici omogućuju učinkovito određivanje izvedivih staza u 3D konfiguracijskom prostoru, koje mogu uključivati prekoračivanje prepreka te prelazak između hodnih površina različitih visina. Okolina robota dijeli se na dva područja. U prvom području može se primijeniti 2D planiranje koraka, dok se složenost 3D planiranja koraka u drugom području može značajno smanjiti tako što se pri planiranju uzima u obzir samo jedan reducirani skup staza, koji je pak dostatan za rješavanje velikog broja praktičnih zadataka

Teaching a robot where doors and drawers are and how to handle them

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.We address the problem of teaching a service robot to detect doors and drawers in indoor environments. We propose a robust and accurate method in which a human demonstrates to the robot how to open doors and drawers that the robot is expected to operate in its future use. The proposed algorithm creates a model of a door or drawer from a sequence of RGB-D images and inserts it into an environment map. The model contains information about the size of the door panel or drawer front, as well as the position and orientation of the joint axis. This augmented environment map is then used by the robot to detect the target object in its environment and estimate its state.This work has been partially supported by the Croatian Science Foundation under the project IP-2019-04-6819; by MCIN/ AEI /10.13039/501100011033 under the project CHLOE-GRAPH (PID2020-119244GB-I00); by MCIN/ AEI /10.13039/501100011033 and by the ”European Union (EU) NextGenerationEU/PRTR under the project ROB-IN (PLEC2021-007859).Peer ReviewedPostprint (author's final draft

Visual servoing for low-cost SCARA robots using an RGB-D camera as the only sensor

Visual servoing with a simple, two-step hand–eye calibration for robot arms in Selective Compliance Assembly Robot Arm configuration, along with the method for simple vision-based grasp planning, is proposed. The proposed approach is designed for low-cost, vision-guided robots, where tool positioning is achieved by visual servoing using marker tracking and depth information provided by an RGB-D camera, without encoders or any other sensors. The calibration is based on identification of the dominant horizontal plane in the camera field of view, and an assumption that all robot axes are perpendicular to the identified plane. Along with the plane parameters, one rotational movement of the shoulder joint provides sufficient information for visual servoing. The grasp planning is based on bounding boxes of simple objects detected in the RGB-D image, which provide sufficient information for robot tool positioning, gripper orientation and opening width. The developed methods are experimentally tested using a real robot arm. The accuracy of the proposed approach is analysed by measuring the positioning accuracy as well as by performing grasping experiments

Detection of dominant planar surfaces in disparity images based on random sampling

U ovom članku ispituje se praktična primjenjivost RANSAC-pristupa za detekciju ravnih površina na slikama dispariteta dobivenim pomoću stereo vizije. Težište istraživanja je primjena u interijerima, gdje je velik dio dominantnih površina jednolično obojen, što predstavlja poseban problem za stereo viziju. Ispitano je nekoliko jednostavnih modifikacija osnovnog RANSAC-algoritma s ciljem utvrđivanja koliko oni mogu poboljšati njegovu učinkovitost. Predložene su dvije jednostavne mjere točnosti rekonstrukcija ravnih površina. Provedeno je eksperimentalno istraživanje na slikama snimljenim sustavom stereo vizije montiranom na mobilnog robota koji se kretao hodnicima fakulteta.In this paper, the applicability of RANSAC-approach to planar surface detection in disparity images obtained by stereo vision is investigated. This study is specially focused on application in indoor environments, where many of the dominant surfaces are uniformly colored, which poses additional difficulties to stereo vision. Several simple modifications to the basic RANSAC-algorithm are examined and improvements achieved by these modifications are evaluated. Two simple performance measures for evaluating the accuracy of planar surface detection are proposed. An experimental study is performed using images acquired by a stereo vision system mounted on a mobile robot moving in an indoor environment