Aerial Robotics – Unmanned Aerial Vehicles in Interaction with the Environment

Defined as technology that provides services and facilitates the execution of tasks (such as observation, inspection, mapping, search and rescue, maintenance, etc.) by using unmanned aerial vehicles equipped with various sensors and actuators, aerial robotics in one of the fastest growing field in research as well as in the industry. While some of the services provided by aerial robots have already been put into practice (for example aerial inspection and aerial mapping), others (like aerial manipulation) are still at the level of laboratory experimentation on account of their complexity. The ability of an aerial robotic system to interact physically with objects within its surroundings completely transforms the way we view applications of unmanned aerial systems in near-Earth environments. This change in paradigm conveying such new functionalities as aerial tactile inspection; aerial repair, construction, and assembly; aerial agricultural care; and aerial urban sanitation requires an extension of current modeling and control techniques as well as the development of novel concepts. In this article we are giving a very brief introduction to the field of aerial robots

Upravljanje sustavom longitudinalne ventilacije cestovnog tunela zasnovano na neizrazitoj logici s prediktivnim modelom

In this paper we describe a control method for longitudinal ventilation of road tunnels. The method consists of two main elements: a) prediction of a number of jet fans and b) fuzzy control of pollutant levels. Based on measurements of traffic intensity and weather conditions and by knowing tunnel parameters, production of CO, NOx and small particles (soot) is predicted. Estimated values of pollutants are then used for calculation of fresh air volume demand, i.e. required air flow is determined. One dimensional force equation is used for estimation of a number of jet fans that would produce a thrust force sufficient to provide calculated air flow. In the same time a fuzzy controller compares measured and requested levels of pollutants and adjusts a predicted number of jet fans in order to keep the pollutant levels within predefined boundaries. The proposed method is tested by simulation and obtained results are compared with a method which was previosly used in the ventilation system of the tunnel Ucka. Finally, the field results from the proposed control method implementation in the tunel Ucka are presented.U ovom članku opisana je metoda upravljanja sustavom longitudinalne ventilacije cestovnih tunela. Metoda se sastoji od dvije glavne cjeline: a) predikcije potrebnog broja aktivnih ventilatora; i b) neizrazitog upravljanja razinom zagađenja zraka u tunelu. Na osnovi mjerenja vremenskih uvjeta i intenziteta prometa kroz tunel, te poznatih parametara tunela, obavlja se predikcija proizvodnje ugljičnog monoksida, dušikovih oksida i krutih čestica iz ispuha vozila. Te procijenjene količine zagađenja se u nastavku koriste za proračun zahtjeva za svježim zrakom, tj. potrebne brzine strujanja zraka kroz tunel. Broj ventilatora s ukupnim potiskom dovoljnim da se postigne to strujanje određuje se iz ravnoteže sila koje djeluju na zračnu masu u tunelu. Istodobno, neizraziti regulator uspoređuje mjerene i zadane vrijednosti zagađenja, te podešava proračunati broj ventilatora kako bi održao stupanj onečišćenja zraka unutar dopuštenih granica. Predložena metoda upravljanja ispitana je simulacijom uz usporedbu s metodom upravljanja koja je dosad korištena u tunelu Učka, a potom su dani rezultati stvarne implementacije predstavljene metode upravljanja na tunelu Učka

Neizrazito adaptivno upravljanje silom dodira slijednih mehanizama s jednim stupnjem slobode gibanja

The paper presents position/force control with a completely fuzzified adaptive force control system for the single degree of freedom servo mechanisms. The proposed force control scheme contains an adaptive fuzzy force controller and a subordinated fuzzy velocity controller. By using a second-order reference model, a model reference-based fuzzy adaptation mechanism is able to keep the error between the model and system output responses within desired limits. The results obtained by computer simulations indicate a stable performance of the force control system for a wide range of environment stiffness variations. The proposed adaptive force control method has also been effective in case of a contact with a rough surface or a complex form workpiece.Članak prikazuje upravljanje položajem/silom dodira slijednog mehanizma s jednim stupnjem slobode gibanja korištenjem neizrazitog adaptivnog sustava upravljanja silom. Predložena shema upravljanja silom dodira sadrži adaptivni neizraziti regulator sile i podređeni neizraziti regulator brzine vrtnje. Koristeći referentni model drugog reda, neizraziti na modelu zasnovani adaptacijski mehanizam u stanju je držati razliku između odziva modela i odziva sustava u zadanim granicama. Rezultati dobiveni numeričkim simulacijama pokazuju stabilno vladanje sustava upravljanja silom dodira za široki raspon varijacija krutosti okoline. Predložena metoda adaptivnog upravljanja silom se pokazala uspješnom i u slučaju dodira s neravnom površinom ili s radnim predmetom složena oblika

Romb Technologies – autonomous navigation in logistics sector

Romb Technologies is an academic spin-off company that commercializes autonomous navigation technologies in the logistics sector. Based on over 40 years of combined R&D experience in robotics and autonomous navigation, the company, founded in November 2018. as a spin-off of the Laboratory for Robotics and Intelligent Control Systems at the Faculty for Electrical Engineering and Computing at the University of Zagreb and incubated at the Zagreb Innovation Centre (ZICER), develops software for accurate and efficient automated material handling activities

Hibridni sustav daljinskog upravljanja lebdjelicom

This article presents one solution to a quadrotor control problem that is based on a discrete automaton. This automaton combines classical PID and more sophisticated LQ controllers to create a hybrid control system. This closed loop control concept is expanded with an open loop controller that enables the aircraft to perform aggressive flying maneuvers. The combination of open and closed loop controllers builds a hybrid controller concept that allows directed and autonomous flying of the quadrotor aerial vehicle. Proposed control concept was tested on an elaborate mathematical model. The article discusses these test results and presents the means to develop such a controller.U radu je opisan hibridni upravljački koncept bespilotne letjelice pogonjene s četiri rotora, koji objedinjuje klasične PID regulatore i naprednije LQ regulatore primjenom Mooreova automata. Takav je hibridni koncept upravljanja u zatvorenoj petlji nadograđen upravljanjem u otvorenoj petlji koje omogućuje ostvarenje agresivnih letačkih manevara. Osim toga, kombinacija upravljanja u otvorenoj I zatvorenoj petlji omogućuje i daljinsko upravljanje letjelicom zasnovano na vizualnoj povratnoj vezi. Predloženi sustav upravljanja letjelicom testiran je na iscrpnom matematičkom modelu letjelice

Brain over Brawn -- Using a Stereo Camera to Detect, Track and Intercept a Faster UAV by Reconstructing Its Trajectory

The work presented in this paper demonstrates our approach to intercepting a faster intruder UAV, inspired by the MBZIRC2020 Challenge 1. By leveraging the knowledge of the shape of the intruder's trajectory we are able to calculate the interception point. Target tracking is based on image processing by a YOLOv3 Tiny convolutional neural network, combined with depth calculation using a gimbal-mounted ZED Mini stereo camera. We use RGB and depth data from ZED Mini to extract the 3D position of the target, for which we devise a histogram-of-depth based processing to reduce noise. Obtained 3D measurements of target's position are used to calculate the position, the orientation and the size of a figure-eight shaped trajectory, which we approximate using lemniscate of Bernoulli. Once the approximation is deemed sufficiently precise, measured by Hausdorff distance between measurements and the approximation, an interception point is calculated to position the intercepting UAV right on the path of the target. The proposed method, which has been significantly improved based on the experience gathered during the MBZIRC competition, has been validated in simulation and through field experiments. The results confirmed that an efficient visual perception module which extracts information related to the motion of the target UAV as a basis for the interception, has been developed. The system is able to track and intercept the target which is 30% faster than the interceptor in majority of simulation experiments. Tests in the unstructured environment yielded 9 out of 12 successful results.Comment: To be published in Field Robotics. UAV-Eagle dataset available at: https://github.com/larics/UAV-Eagl

Decentralized Multi-Robot Formation Control Using Reinforcement Learning

This paper presents a decentralized leader-follower multi-robot formation control based on a reinforcement learning (RL) algorithm applied to a swarm of small educational Sphero robots. Since the basic Q-learning method is known to require large memory resources for Q-tables, this work implements the Double Deep Q-Network (DDQN) algorithm, which has achieved excellent results in many robotic problems. To enhance the system behavior, we trained two different DDQN models, one for reaching the formation and the other for maintaining it. The models use a discrete set of robot motions (actions) to adapt the continuous nonlinear system to the discrete nature of RL. The presented approach has been tested in simulation and real experiments which show that the multi-robot system can achieve and maintain a stable formation without the need for complex mathematical models and nonlinear control laws.Comment: 7 pages, 10 figures. To be published in 2023 International Conference on Information, Communication and Automation Technologies (ICAT