Integration of an External Sensors to the System Bioloid

Import 23/07/2015Bakalářská práce se zabývá tématem integrace senzorů zrychlení a svalové aktivity do robotického systému Bioloid. V práci byla provedena analýza technologií použitých v senzorech a sadě Bioloid, a také standardních možností integrace dodatečných senzorů do sady. Na základě požadavků na systém byly navrhnuty varianty řešení, které by je splňovali. Pomocí metody hodnotové analýzy byla vybrána optimální varianta, která dále byla detailně rozpracována. Byl vytvořen prototyp systému a také jeho softwarové zabezpečení. Provedené testy ukázaly, že systém splňuje požadavky.The bachelor thesis deals with a topic of integration of sensors of acceleration and the activity of human muscles to the robotic system Bioloid. In this work were analyzed technologies, used in the sensors and the set Bioloid, as well as the standard possibilities of integration of additional sensors to the set. Based on the requirements to the system, were suggested solutions, which would pass them. Based on value analysis was chosen the optimal solution, which was then developed in detail. The prototype of the system as well as software to it were also made out. The conducted tests had shown that the system fulfills the requirements.354 - Katedra robotikyvýborn

Genetic optimization of a manipulator: Comparison between straight, rounded, and curved mechanism links

There are several ubiquitous kinematic structures that are used in industrial robots, with the most prominent being a six-axis angular structure. However, researchers are experimenting with task-based mechanism synthesis that could provide higher efficiency with custom optimized manipulators. Many studies have focused on finding the most efficient optimization algorithm for task-based robot manipulators. These manipulators, however, are usually optimized from simple modular joints and links, without exploring more elaborate modules. Here, we show that link modules defined by small numbers of parameters have better performance than more complicated ones. We compare four different manipulator link types, namely basic predefined links with fixed dimensions, straight links that can be optimized for different lengths, rounded links, and links with a curvature defined by a Hermite spline. Manipulators are then built from these modules using a genetic algorithm and are optimized for three different tasks. The results demonstrate that manipulators built from simple links not only converge faster, which is expected given the fewer optimized parameters, but also converge on lower cost values.Web of Science116art. no. 247

Generating synthetic depth image dataset for industrial applications of hand localization

In this paper, we focus on the problem of applying domain randomization to produce synthetic datasets for training depth image segmentation models for the task of hand localization. We provide new synthetic datasets for industrial environments suitable for various hand tracking applications, as well as ready-to-use pre-trained models. The presented datasets are analyzed to evaluate the characteristics of these datasets that affect the generalizability of the trained models, and recommendations are given for adapting the simulation environment to achieve satisfactory results when creating datasets for specialized applications. Our approach is not limited by the shortcomings of standard analytical methods, such as color, specific gestures, or hand orientation. The models in this paper were trained solely on a synthetic dataset and were never trained on real camera images; nevertheless, we demonstrate that our most diverse datasets allow the models to achieve up to 90% accuracy. The proposed hand localization system is designed for industrial applications where the operator shares the workspace with the robot.Web of Science10997449973

Improved mutual understanding for human-robot collaboration: Combining human-aware motion planning with haptic feedback devices for communicating planned trajectory

In a collaborative scenario, the communication between humans and robots is a fundamental aspect to achieve good efficiency and ergonomics in the task execution. A lot of research has been made related to enabling a robot system to understand and predict human behaviour, allowing the robot to adapt its motion to avoid collisions with human workers. Assuming the production task has a high degree of variability, the robot's movements can be difficult to predict, leading to a feeling of anxiety in the worker when the robot changes its trajectory and approaches since the worker has no information about the planned movement of the robot. Additionally, without information about the robot's movement, the human worker cannot effectively plan own activity without forcing the robot to constantly replan its movement. We propose a novel approach to communicating the robot's intentions to a human worker. The improvement to the collaboration is presented by introducing haptic feedback devices, whose task is to notify the human worker about the currently planned robot's trajectory and changes in its status. In order to verify the effectiveness of the developed human-machine interface in the conditions of a shared collaborative workspace, a user study was designed and conducted among 16 participants, whose objective was to accurately recognise the goal position of the robot during its movement. Data collected during the experiment included both objective and subjective parameters. Statistically significant results of the experiment indicated that all the participants could improve their task completion time by over 45% and generally were more subjectively satisfied when completing the task with equipped haptic feedback devices. The results also suggest the usefulness of the developed notification system since it improved users' awareness about the motion plan of the robot.Web of Science2111art. no. 367

Distributed camera subsystem for obstacle detection

This work focuses on improving a camera system for sensing a workspace in which dynamic obstacles need to be detected. The currently available state-of-the-art solution (MoveIt!) processes data in a centralized manner from cameras that have to be registered before the system starts. Our solution enables distributed data processing and dynamic change in the number of sensors at runtime. The distributed camera data processing is implemented using a dedicated control unit on which the filtering is performed by comparing the real and expected depth images. Measurements of the processing speed of all sensor data into a global voxel map were compared between the centralized system (MoveIt!) and the new distributed system as part of a performance benchmark. The distributed system is more flexible in terms of sensitivity to a number of cameras, better framerate stability and the possibility of changing the camera number on the go. The effects of voxel grid size and camera resolution were also compared during the benchmark, where the distributed system showed better results. Finally, the overhead of data transmission in the network was discussed where the distributed system is considerably more efficient. The decentralized system proves to be faster by 38.7% with one camera and 71.5% with four cameras.Web of Science2212art. no. 458

Influence of drift on robot repeatability and its compensation

This paper presents an approach to compensate for the effect of thermal expansion on the structure of an industrial robot and thus to reduce the repeatability difference of the robot in cold and warm conditions. In contrast to previous research in this area that deals with absolute accuracy, this article is focused on determining achievable repeatability. To unify and to increase the robot repeatability, the measurements with highly accurate sensors were performed under different conditions on an industrial robot ABB IRB1200, which was equipped with thermal sensors, mounted on a pre-defined position around joints. The performed measurements allowed to implement a temperature-based prediction model of the end effector positioning error. Subsequent tests have shown that the implemented model used for the error compensation proved to be highly effective. Using the methodology presented in this article, the impact of drift can be reduced by up to 89.9%. A robot upgraded with a compensation principle described in this article does not have to be warmed up as it works with the same low repeatability error in the entire range of the achievable temperatures.Web of Science1122art. no. 1081

Biped robot with unconventional kinematics

The article deals with the design of a robot with an unconventional kinematic structure, which is able to vertically stabilize the position of the robot base for the placement of sensors and handling superstructures. The robot concept was designed to have as few actuators as possible. The robot's kinematics was solved for the purpose of simulating the robot's movement and implementation into the robot's control system.Web of Science20225824581

Teleoperačne řízený humanoidní robot

This thesis deals with a topic of designing of a teleoperated humanoid robot. The main idea is to create a semi-autonomous robotic system that repeats movements of its operator. At first, an analysis of actual state of problematics of the teleoperated humanoid robots and body pose estimation methods was conducted. Then, based on requirements to the system a technical solution of teleoperated humanoid robotic system was designed. As base for developing of the robotic system a Bioloid humanoid robot was used. For operator’s body pose estimation a Kinect sensor was applied. The robotic system is divided into two parts: a part of the operator and a part of the robot. For both parts of the system software solutions were developed. Based on developed mathematical model of the robot, a software implementation of the algorithms of calculation of the mass center and detection of self-collision were made. Both algorithms were optimized, verified and run in real-time on Netduino board - main controller of the robot. For virtual visualization of the system a virtual model of the robot in V-Rep application was used. Conducted tests shown that system fulfills the requirements and the robot correctly repeats movements of the operator.Tato diplomová práce se zabývá problematikou navrhování teleoperačně řízeného humanoidního robota. Hlavní myšlenkou je vytvoření poloautonomního robotického systému, který opakuje pohyby svého operátora. Zpočátku se provedla analýza aktuálního stavu problematiky teleoperačně řízených humanoidních robotů a metod rozpoznávaní pohybů lidského těla. Na základě požadavků na systém bylo navrženo technické řešení teleoperačně řízeného robotického systému. Jako základ pro vývoj systému byl použit humanoidní robot Bioloid. Pro vyhodnocení pohybů těla operátora byl použit snímač Kinect. Robotický systém je rozdělen na dvě části: část obsluhy a součást robota. Pro obě části systému bylo vyvinuto softwarové řešení. Na základě vyvinutého matematického modelu robota byla provedena softwarová implementace algoritmů výpočtu těžiště a detekce kolize robotu s vlastními částmi. Oba algoritmy byly optimalizovány, ověřeny a jsou vypočítávány v reálném čase na Netduino – hlavní řídicí desce robota. Pro virtuální vizualizaci systému byl použit virtuální model robota v aplikaci V-Rep. Provedené testy ukázaly, že systém splňuje požadavky a robot správně opakuje pohyby svého operátoru.354 - Katedra robotikyvýborn

Plánování pohybu manipulátoru v dynamickém prostředí při využití informací z RGB-D senzoru

The presented dissertation deals with the topic of trajectory planning of a manipulator in a dynamic environment using data from the RGB-D sensor. An example of such a dynamic environment is a shared workspace where a robot interacts with human workers. Cooperation between robot and human is a widespread topic within the concept of Industry 4.0, which opens up the possibility of creating workplaces with robots that can come into direct contact with employees during the work cycle. Such collaboration brings new opportunities to improve ergonomics and options for manufacturing automation. However, it also carries the risks associated with the possibility of a robot colliding with a human. Adaptive behaviour of the robot - replanning the trajectory with respect to the operator’s current position - can increase the efficiency and safety of cooperation since the robot will be able to avoid collisions and proceed in task completion. In such a situation, however, the user cannot know in advance what the robot’s trajectory will look like after replanning, which can cause discomfort along with reducing efficiency when interacting with the robot. The research in this work focuses on the topic of motion planning and communication of the robot motion plan to a human worker during cooperation in a shared workspace. The requirement is not only a theoretical exploration of possibilities but also a practical implementation in the form of an experimental workplace to verify the proposed principles. The introductory part of the thesis analyses the current state of the art in the field of path planning, motion planning frameworks, environment perception, approaches to improving mutual awareness during human-robot cooperation and implementation of haptic feedback devices. The main contribution of the research is the concept of a novel collaborative system, which combines rapid robot path planning with the system for notifying the user about the currently planned path of the robot and its status. The principles of the system are implemented and tested on an experimental workspace. The robot’s path planning system is based on a motion planning framework optimized for better performance in a set of tasks simulated in a virtual environment. It is hypothesized that the use of the proposed notification system during human-robot collaboration will improve the overall performance, awareness about the planned robot trajectory and encourage a positive experience to the human user. In order to test this hypothesis, a user study is performed, and its data are statistically analysed. The results indicate the potential of the developed haptic notification-based approach in improving mutual understanding during human-robot interaction. The topic of the work is relevant for the deployment of collaborative robots in industrial tasks and aims at improving the effectiveness of human-robot cooperation.Předložená disertační práce se zabývá tématem plánování trajektorie manipulátoru v dynamickém prostředí s využitím dat z RGB-D senzoru. Příkladem takového dynamického prostředí je sdílený pracovní prostor, kde robot spolupracuje s člověkem. Spolupráce mezi robotem a člověkem je aktuálním tématem v rámci konceptu Průmysl 4.0, otevírající možnost vytváření pracovišť s roboty, které mohou během pracovního cyklu přicházet do přímého kontaktu se zaměstnanci. Taková spolupráce přináší nové příležitosti ke zlepšení ergonomie a možností automatizace výroby. To se sebou však nese také rizika spojená s možností kolize robotu s člověkem. Adaptivní chování robotu – přeplánování trajektorie s ohledem na aktuální polohu operátora – může zvýšit efektivitu a bezpečnost spolupráce, protože robot bude schopen zabránit kolizím a pokračovat v dokončení úkolu. V takové situaci však uživatel nemůže předem vědět, jak bude trajektorie robotu vypadat po přeplánování, což může při interakci s robotem způsobit diskomfort a spolu s tím snížení efektivity. Výzkum v této práci se zaměřuje na téma plánování pohybu robotu a informování člověka o pohybu robotu během spolupráce ve sdíleném pracovním prostoru. Požadavkem je nejen teoretické zkoumání možností, ale také praktická realizace experimentálního pracoviště k ověření navržených principů. Úvodní část práce analyzuje současný stav v oblasti plánování trajektorií, frameworků plánování pohybu robotů, vnímání prostředí, přístupů ke zlepšení vzájemného povědomí během spolupráce člověk-robot a implementace zařízení taktilní zpětné vazby. Hlavním přínosem výzkumu je koncept nového kolaborativního systému, který kombinuje rychlé plánování trajektorie robotu se systémem pro upozornění uživatele na tuto plánovanou trajektorii robotu a jeho současný stav. Principy systému jsou implementovány a testovány na experimentálním kolaborativním pracovišti. Systém plánování trajektorie robotu je založen na frameworku plánování pohybu optimalizovaném pro lepší výkon v sadě úkolů simulovaných ve virtuálním prostředí. Předpokládá se, že použití navrhovaného notifikačního systému během spolupráce člověka s robotem zlepší celkový výkon, povědomí o plánované trajektorii robotu a podpoří pozitivní vnímání úlohy u člověka. Za účelem testování této hypotézy je prováděna uživatelská studie a její data jsou statisticky zpracovaná a analyzovaná. Výsledky ukazují potenciál vyvinutého přístupu pro zlepšování kvality interakce při spolupráci člověk-robot. Téma práce je relevantní pro nasazení spolupracujících robotů v průmyslových úlohách a zaměřuje se na zlepšení efektivity spolupráce člověka a robotu.354 - Katedra robotikyvyhově

Teleoperated Humanoid Robot

Article describes technical solution of teleoperated humanoid robotic system. To acquire position data of operator’s body Kinect sensor is used. In article are described mathematical equations used to transform data from Kinect sensor to positions of each servomotor of the robot. Article also describes software and electric structure for both components of the system: robot and operator’s PC. All software solutions are developed using C#. For dynamic simulation of the system a detailed model of the robot has been created in V-Rep, simulation receives same data as real robot