An Evaluation of Three Different Infield Navigation Algorithms

In this chapter, we present and evaluate three different infield navigation algorithms, based on the readings from a LIDAR sensor. All three algorithms are tested on a small field robot and used to autonomously drive the robot between the two adjacent rows of maze plants. The first algorithm is the simplest one and just takes distance readings from the left and right side. If robot is not in the center of the mid-row space, it adjusts its course by turning the robot in the right direction accordingly. The second approach groups the left and right readings into two vertical lines by using least-square fit approach. According to the calculated distance and orientation to both lines, it adjusts the course of the robot. The third approach tries to fit an optimal triangle between the robot and the plants, revealing the most optimal one. Based on its shape, the course of the robot is adjusted. All three algorithms are tested in a simulated (ROS stage) and then in an outdoor (maze test field) environment comparing the optimal line with the actual calculated position of the robot. The tests prove that all three approaches work with an error of 0.041 ± 0.034 m for the first algorithm, 0.07 ± 0.059 m for the second, and 0.078 ± 0.055 m error for the third

A flexible hardware-in-the-loop architecture for UAVs

© 20xx 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.As robotic technology matures, fully autonomous robots become a realistic possibility, but demand very complex solutions to be rapidly engineered. In order to be able to quickly set up a working autonomous system, and to reduce the gap between simulated and real experiments, we propose a modular, upgradeable and flexible hardware-in-the-loop (HIL) architecture, which hybridizes the simulated and real settings. We take as use case the autonomous exploration of dense forests with UAVs, with the aim of creating useful maps for forest inspection, cataloging, or to compute other metrics such as total wood volume. As the first step in the development of the full system, in this paper we implement a fraction of this architecture, comprising assisted localization, and automatic methods for mapping, planning and motion execution. Specifically we are able to simulate the use of a 3D LIDAR endowed below an actual UAV autonomously navigating among simulated obstacles, thus the platform safety is not compromised. The full system is modular and takes profit of pieces either publicly available or easily programmed. We highlight the flexibility of the proposed HIL architecture to rapidly configure different experimental setups with a UAV in challenging terrain. Moreover, it can be extended to other robotic fields without further design. The HIL system uses the multi-platform ROS capabilities and only needs a motion capture system as external extra hardware, which is becoming standard equipment in all research labs dealing with mobile robots.Peer ReviewedPostprint (author's final draft

THE USAGE OF COMPUTER VISION FOR CONTROLLING AND MANAGEMENT OF MOBILE PLATFORM

Diplomsko delu pred vami govori o računalniškem vidu, kateri v današnjem času, času tehnološkega razcveta, postaja vedno bolj aktualen. Na prvih straneh so predstavljene znane rešitve in uporaba računalniškega vida v vsakdanjem življenju, njegova uporaba v vojski, proizvodnji, avtomobilistični in kmetijski industriji. Nato so opisani znani postopki in algoritmi digitalne obdelave slik. Sledi podrobnejši opis avtomatiziranega poljedelskega stroja in uporabljenih algoritmov, ki so bili razviti za njegovo delovanje. Za konec so predstavljeni rezultati izsledkov delovanja avtomatiziranega poljedelskega stroja v kontroliranih in nekontroliranih pogojih. Delo zaključuje sklep in predstavitev možnosti uporabe računalniškega vida v prihodnosti.This diploma thesis introduces a field of computer vision, a field that is becoming more and more popular. On the first pages, we discuss known techniques and usage scenarios of a computer vision that can be used in everyday life, military, car or even in agricultural industry. We introduce known digital image processing algorithms that were used to develop a prototype of the autonomous field robot. At the end, we test the robot, first in controlled and then in uncontrolled environment. We sum up with some of the findings and lay down a plan for future research in the field of computer vision

Systems and control for autonomous mobile robots in cluttered environments

Avtonomna mobilna robotika je uporabna v nadzornih sistemih in kot pomoč pri iskanju in reševanju žrtev v primeru nesreč. Regulacija hitrosti modularnega avtonomnega sistema za pomoč pri reševanju ob naravnih nesrečah ima veliko težo, saj je bistvena za pravilno gibanje v prostoru. Ena izmed pomembnih nalog v avtonomni robotiki je regulacija hitrosti (linearne in kotne), ki jo proizvede avtonomni sistem za mobilno bazo. Naš glavni cilj je ustvariti hitrostni regulator na višjem nivoju, ki ga je mogoče uporabiti na različnih mobilnih platformah. V tem primeru se osredotočamo na mobilne robote z diferencialnim pogonom. Naš pristop sloni na iskanju ujemanja krožnic, ki upošteva kinematični model in omejitve mobilne baze robota. Na podlagi algoritma se izvede trajektorija, ta je odvisna od nastavljenih parametrov, ki so prilagojeni za mobilno bazo. Dodatno smo v algoritem vključili poravnavo kota orientacije in kompenzacijo naklona kota med gibanjem mobilnega robota. Opisali smo našega reševalnega robota in sisteme za avtonomno delovanje in implementacijo algoritmov. Predlagan algoritem za sledenje smo primerjali z algoritmom Hector. Prikazani so rezultati primerjav in rezultati sledenja mobilnega robota v simulacijah in realnih eksperimentih. Nato smo nadaljevali naše delo z implementacijo našega algoritma na brezpilotnih letečih vozilih, kjer smo zgradili kompletno simulacijo z možnostjo vključitve pravega letečega vozila. Na tem sistemu smo izvedli serijo eksperimentov, da bi dokazali koncept sistema.Many applications such as surveillance, inspection, search and rescue operations can be performed with autonomous robots. Our aim is to control a modular autonomous system in rescuing robotics. One of the basic problems regarding autonomous robotics is the execution part in which the control commands (translation and rotational velocities) are produced for mobile bases. We have focused on this area because for skid-steered mobile robots there is available only a small amount of path following software. Our goal was to develop a velocity controller that could be used for multiple skid-steered mobile bases. We considered differential drive mobile bases such as tracked skid-steering mobile base. Our approach is based on an arc fitting algorithm which takes into account the robot constrains and kinematical model. It produces continuous trajectory where fitting to the given path depends on given parameters adapted to the mobile base. Moreover, we have included orientation angle compensation while the mobile robot is moving, and ground inclination compensation. Our rescue robot is described together with the simulation setup and algorithm implementation. We compared our algorithm to the Hector-based software. We showed the results of the compared algorithms and the results of mobile robot path following in simulation and real experiments. Later on we used our algorithm on an unmanned aerial vehicle platformwe have built a simulation in which real aerial vehicle could be included. On this system setup we performed a series of experiments to prove the concept

Dynamic arc fitting path follower for skid-steered mobile robots

Many applications, such as surveillance, inspection or search and rescue operations, can be performed with autonomous robots. Our aim is a control of modular autonomous systems in rescue robotics. One of the basic problems with autonomous robotics is the execution part where the control commands (translation and rotational velocities) are produced for mobile bases. Therefore we have focused on this area because there is only a small amount of available path following software for skid-steered mobile robots. Our goal was to develop a velocity controller that could be used for multiple skid-steered mobile bases. We considered differential drive mobile bases such as tracked skid-steering mobile bases. Our approach is based on an arc fitting algorithm, which takes into account the robot constraints and kinematical model. It produces a continuous trajectory where fitting to the given path is adapted based on given parameters. Moreover, we have included orientation angle compensation while the mobile robot is moving and ground inclination compensation. Our rescue robot is described, together with the simulation setup and algorithm implementation. We compared our algorithm to the Hector-based software and curvature velocity approach. The results for the proposed algorithm are shown for the simulation results and the experiment