CompaRob: the shopping cart assistance robot

Technology has recently been developed which offers an excellent opportunity to design systems with the ability to help people in their own houses. In particular, assisting elderly people in their environments is something that can significantly improve their quality of life. However, helping elderly people outside their usual environment is also necessary, to help them to carry out daily tasks like shopping. In this paper we present a person-following shopping cart assistance robot, capable of helping elderly people to carry products in a supermarket. First of all, the paper presents a survey of related systems that perform this task, using different approaches, such as attachable modules and computer vision. After that, the paper describes in detail the proposed system and its main features. The cart uses ultrasonic sensors and radio signals to provide a simple and effective person localization and following method. Moreover, the cart can be connected to a portable device like a smartphone or tablet, thus providing ease of use to the end user. The prototype has been tested in a grocery store, while simulations have been done to analyse its scalability in larger spaces where multiple robots could coexist.This work was partly supported by Spanish Ministry under Grant DPI2014-57746-C3 (MERBOTS Project) and by Universitat Jaume I Grants P1-1B2015-68 and PID2010-12

소형동물의 뇌신경 자극을 위한 완전 이식형 신경자극기

학위논문(박사)--서울대학교 대학원 :공과대학 전기·정보공학부,2020. 2. 김성준.In this study, a fully implantable neural stimulator that is designed to stimulate the brain in the small animal is described. Electrical stimulation of the small animal is applicable to pre-clinical study, and behavior study for neuroscience research, etc. Especially, behavior study of the freely moving animal is useful to observe the modulation of sensory and motor functions by the stimulation. It involves conditioning animal's movement response through directional neural stimulation on the region of interest. The main technique that enables such applications is the development of an implantable neural stimulator. Implantable neural stimulator is used to modulate the behavior of the animal, while it ensures the free movement of the animals. Therefore, stable operation in vivo and device size are important issues in the design of implantable neural stimulators. Conventional neural stimulators for brain stimulation of small animal are comprised of electrodes implanted in the brain and a pulse generation circuit mounted on the back of the animal. The electrical stimulation generated from the circuit is conveyed to the target region by the electrodes wire-connected with the circuit. The devices are powered by a large battery, and controlled by a microcontroller unit. While it represents a simple approach, it is subject to various potential risks including short operation time, infection at the wound, mechanical failure of the device, and animals being hindered to move naturally, etc. A neural stimulator that is miniaturized, fully implantable, low-powered, and capable of wireless communication is required. In this dissertation, a fully implantable stimulator with remote controllability, compact size, and minimal power consumption is suggested for freely moving animal application. The stimulator consists of modular units of surface-type and depth-type arrays for accessing target brain area, package for accommodating the stimulating electronics all of which are assembled after independent fabrication and implantation using customized flat cables and connectors. The electronics in the package contains ZigBee telemetry for low-power wireless communication, inductive link for recharging lithium battery, and an ASIC that generates biphasic pulse for neural stimulation. A dual-mode power-saving scheme with a duty cycling was applied to minimize the power consumption. All modules were packaged using liquid crystal polymer (LCP) to avoid any chemical reaction after implantation. To evaluate the fabricated stimulator, wireless operation test was conducted. Signal-to-Noise Ratio (SNR) of the ZigBee telemetry were measured, and its communication range and data streaming capacity were tested. The amount of power delivered during the charging session depending on the coil distance was measured. After the evaluation of the device functionality, the stimulator was implanted into rats to train the animals to turn to the left (or right) following a directional cue applied to the barrel cortex. Functionality of the device was also demonstrated in a three-dimensional maze structure, by guiding the rats to navigate better in the maze. Finally, several aspects of the fabricated device were discussed further.본 연구에서는 소형 동물의 두뇌를 자극하기 위한 완전 이식형 신경자극기가 개발되었다. 소형 동물의 전기자극은 전임상 연구, 신경과학 연구를 위한 행동연구 등에 활용된다. 특히, 자유롭게 움직이는 동물을 대상으로 한 행동 연구는 자극에 의한 감각 및 운동 기능의 조절을 관찰하는 데 유용하게 활용된다. 행동 연구는 두뇌의 특정 관심 영역을 직접적으로 자극하여 동물의 행동반응을 조건화하는 방식으로 수행된다. 이러한 적용을 가능케 하는 핵심기술은 이식형 신경자극기의 개발이다. 이식형 신경자극기는 동물의 움직임을 방해하지 않으면서도 그 행동을 조절하기 위해 사용된다. 따라서 동물 내에서의 안정적인 동작과 장치의 크기가 이식형 신경자극기를 설계함에 있어 중요한 문제이다. 기존의 신경자극기는 두뇌에 이식되는 전극 부분과, 동물의 등 부분에 위치한 회로부분으로 구성된다. 회로에서 생산된 전기자극은 회로와 전선으로 연결된 전극을 통해 목표 지점으로 전달된다. 장치는 배터리에 의해 구동되며, 내장된 마이크로 컨트롤러에 의해 제어된다. 이는 쉽고 간단한 접근방식이지만, 짧은 동작시간, 이식부위의 감염이나 장치의 기계적 결함, 그리고 동물의 자연스러운 움직임 방해 등 여러 문제점을 야기할 수 있다. 이러한 문제의 개선을 위해 무선통신이 가능하고, 저전력, 소형화된 완전 이식형 신경자극기의 설계가 필요하다. 본 연구에서는 자유롭게 움직이는 동물에 적용하기 위하여 원격 제어가 가능하며, 크기가 작고, 소모전력이 최소화된 완전이식형 자극기를 제시한다. 설계된 신경자극기는 목표로 하는 두뇌 영역에 접근할 수 있는 표면형 전극과 탐침형 전극, 그리고 자극 펄스 생성 회로를 포함하는 패키지 등의 모듈들로 구성되며, 각각의 모듈은 독립적으로 제작되어 동물에 이식된 뒤 케이블과 커넥터로 연결된다. 패키지 내부의 회로는 저전력 무선통신을 위한 지그비 트랜시버, 리튬 배터리의 재충전을 위한 인덕티브 링크, 그리고 신경자극을 위한 이상성 자극파형을 생성하는 ASIC으로 구성된다. 전력 절감을 위해 두 개의 모드를 통해 사용률을 조절하는 방식이 장치에 적용된다. 모든 모듈들은 이식 후의 생물학적, 화학적 안정성을 위해 액정 폴리머로 패키징되었다. 제작된 신경자극기를 평가하기 위해 무선 동작 테스트가 수행되었다. 지그비 통신의 신호 대 잡음비가 측정되었으며, 해당 통신의 동작거리 및 데이터 스트리밍 성능이 검사되었고, 장치의 충전이 수행될 때 코일간의 거리에 따라 전송되는 전력의 크기가 측정되었다. 장치의 평가 이후, 신경자극기는 쥐에 이식되었으며, 해당 동물은 이식된 장치를 이용해 방향 신호에 따라 좌우로 이동하도록 훈련되었다. 또한, 3차원 미로 구조에서 쥐의 이동방향을 유도하는 실험을 통하여 장치의 기능성을 추가적으로 검증하였다. 마지막으로, 제작된 장치의 특징이 여러 측면에서 심층적으로 논의되었다.Chapter 1 : Introduction 1 1.1. Neural Interface 2 1.1.1. Concept 2 1.1.2. Major Approaches 3 1.2. Neural Stimulator for Animal Brain Stimulation 5 1.2.1. Concept 5 1.2.2. Neural Stimulator for Freely Moving Small Animal 7 1.3. Suggested Approaches 8 1.3.1. Wireless Communication 8 1.3.2. Power Management 9 1.3.2.1. Wireless Power Transmission 10 1.3.2.2. Energy Harvesting 11 1.3.3. Full implantation 14 1.3.3.1. Polymer Packaging 14 1.3.3.2. Modular Configuration 16 1.4. Objectives of This Dissertation 16 Chapter 2 : Methods 18 2.1. Overview 19 2.1.1. Circuit Description 20 2.1.1.1. Pulse Generator ASIC 21 2.1.1.2. ZigBee Transceiver 23 2.1.1.3. Inductive Link 24 2.1.1.4. Energy Harvester 25 2.1.1.5. Surrounding Circuitries 26 2.1.2. Software Description 27 2.2. Antenna Design 29 2.2.1. RF Antenna 30 2.2.1.1. Design of Monopole Antenna 31 2.2.1.2. FEM Simulation 31 2.2.2. Inductive Link 36 2.2.2.1. Design of Coil Antenna 36 2.2.2.2. FEM Simulation 38 2.3. Device Fabrication 41 2.3.1. Circuit Assembly 41 2.3.2. Packaging 42 2.3.3. Electrode, Feedthrough, Cable, and Connector 43 2.4. Evaluations 45 2.4.1. Wireless Operation Test 46 2.4.1.1. Signal-to-Noise Ratio (SNR) Measurement 46 2.4.1.2. Communication Range Test 47 2.4.1.3. Device Operation Monitoring Test 48 2.4.2. Wireless Power Transmission 49 2.4.3. Electrochemical Measurements In Vitro 50 2.4.4. Animal Testing In Vivo 52 Chapter 3 : Results 57 3.1. Fabricated System 58 3.2. Wireless Operation Test 59 3.2.1. Signal-to-Noise Ratio Measurement 59 3.2.2. Communication Range Test 61 3.2.3. Device Operation Monitoring Test 62 3.3. Wireless Power Transmission 64 3.4. Electrochemical Measurements In Vitro 65 3.5. Animal Testing In Vivo 67 Chapter 4 : Discussion 73 4.1. Comparison with Conventional Devices 74 4.2. Safety of Device Operation 76 4.2.1. Safe Electrical Stimulation 76 4.2.2. Safe Wireless Power Transmission 80 4.3. Potential Applications 84 4.4. Opportunities for Further Improvements 86 4.4.1. Weight and Size 86 4.4.2. Long-Term Reliability 93 Chapter 5 : Conclusion 96 Reference 98 Appendix - Liquid Crystal Polymer (LCP) -Based Spinal Cord Stimulator 107 국문 초록 138 감사의 글 140Docto

Estado del arte en robótica cooperativa aplicada al rescate de víctimas

The present article, in the context of a documentary research carried out and interpreted to be taken as a baseline in research for the ROMA Autonomous Mobile Robotics Group of the Francisco José de Caldas District University, describes the state of art of the applied RC to the rescue of victims. The revision is established chronologically in the last fifteen years; in Latin America; and focused mainly in Colombia. They are used as sources: The Google Schoolar database, and articles from the electronic engineering journals indexed for the year 2017 in COLCIENCIAS. As a product thrown, a particular model of communication technology used in CR is presented in the Colombian context.El presente artículo, en el contexto de una investigación documental realizada e interpretada para que fuera tomada como línea de base en investigaciones para el grupo de Robótica Móvil Autónoma ROMA de la Universidad Distrital Francisco José de Caldas, describe el estado de arte de la RC aplicada al rescate de víctimas. Se establece cronológicamente la revisión en los últimos quince años; en Latinoamérica; y enfocada principalmente en Colombia. Se utilizan como fuentes: la base de datos Google Schoolar, y artículos de las revistas de Ingeniería electrónica indexadas para el año 2017 en COLCIENCIAS. Como producto arrojado se presenta un modelo particular de la tecnología de comunicación empleada en RC en el contexto colombiano

Sensor Fusion for Mobile Robot Localization using UWB and ArUco Markers

Uma das principais características para considerar um robô autónomo é o facto de este ser capaz de se localizar, em tempo real, no seu ambiente, ou seja saber a sua posição e orientação. Esta é uma área desafiante que tem sido estudada por diversos investigadores em todo o mundo. Para obter a localização de um robô é possível recorrer a diferentes metodologias. No entanto há metodologias que apresentam problemas em diferentes circunstâncias, como é o caso da odometria que sofre de acumulação de erros com a distância percorrida pelo robô. Outro problema existente em diversas metodologias é a incerteza na deteção do robô devido a ruído presente nos sensores. Com o intuito de obter uma localização mais robusta do robô e mais tolerante a falhas é possível combinar diversos sistemas de localização, combinando assim as vantagens de cada um deles. Neste trabalho, será utilizado o sistema Pozyx, uma solução de baixo custo que fornece informação de posicionamento com o auxílio da tecnologia Ultra-WideBand Time-of-Flight (UWB ToF). Também serão utilizados marcadores ArUco colocados no ambiente que através da sua identificação por uma câmara é também possível obter informação de posicionamento. Estas duas soluções irão ser estudadas e implementadas num robô móvel, através de um esquema de localização baseada em marcadores. Primeiramente, irá ser feita uma caracterização do erro de ambos os sistemas, uma vez que as medidas não são perfeitas, havendo sempre algum ruído nas medições. De seguida, as medidas fornecidas pelos sistemas irão ser filtradas e fundidas com os valores da odometria do robô através da implementação de um Filtro de Kalman Extendido (EKF). Assim, é possível obter a pose do robô (posição e orientação), pose esta que é comparada com a pose fornecida por um sistema de Ground-Truth igualmente desenvolvido para este trabalho com o auxílio da libraria ArUco, percebendo assim a precisão do algoritmo desenvolvido. O trabalho desenvolvido mostrou que com a utilização do sistema Pozyx e dos marcadores ArUco é possível melhorar a localização do robô, o que significa que é uma solução adequada e eficaz para este fim.One of the main characteristics to consider a robot truly autonomous is the fact that it is able to locate itself, in real time, in its environment, that is, to know its position and orientation. This is a challenging area that has been studied by several researchers around the world. To obtain the localization of a robot it is possible to use different methodologies. However, there are methodologies that present problems in different circumstances, as is the case of odometry that suffers from error accumulation with the distance traveled by the robot. Another problem existing in several methodologies is the uncertainty in the sensing of the robot due to noise present in the sensors. In order to obtain a more robust localization of the robot and more fault tolerant it is possible to combine several localization systems, thus combining the advantages of each one. In this work, the Pozyx system will be used, a low-cost solution that provides positioning information through Ultra-WideBand Time-of-Flight (UWB ToF) technology. It will also be used ArUco markers placed in the environment that through their identification by a camera it is also possible to obtain positioning information. These two solutions will be studied and implemented in a mobile robot, through a beacon-based localization scheme. First, an error characterization of both systems will be performed, since the measurements are not perfect, and there is always some noise in the measurements. Next, the measurements provided by the systems will be filtered and fused with the robot's odometry values by the implementation of an Extended Kalman Filter (EKF). In this way, it is possible to obtain the robot's pose, i.e position and orientation, which is compared with the pose provided by a Ground-Truth system also developed for this work with the aid of the ArUco library, thus realizing the accuracy of the developed algorithm. The developed work showed that with the use of the Pozyx system and ArUco markers it is possible to improve the robot localization, meaning that it is an adequate and effective solution for this purpose

Design of autonomous sustainable unmanned aerial vehicle - A novel approach to its dynamic wireless power transfer

A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy.Electric UAVs are presently being used widely in civilian duties such as security, surveillance, and disaster relief. The use of Unmanned Aerial Vehicle (UAV) has increased dramatically over the past years in different areas/fields such as marines, mountains, wild environments. Nowadays, there are many electric UAVs development with fast computational speed and autonomous flying has been a reality by fusing many sensors such as camera tracking sensor, obstacle avoiding sensor, radar sensor, etc. But there is one main problem still not able to overcome which is power requirement for continuous autonomous operation. When the operation needs more power, but batteries can only give for 20 to 30 mins of flight time. These types of system are not reliable for long term civilian operation because we need to recharge or replace batteries by landing the craft every time when we want to continue the operation. The large batteries also take more loads on the UAV which is also not a reliable system. To eliminate these obstacles, there should a recharging wireless power station in ground which can transmit power to these small UAVs wirelessly for long term operation. There will be camera attached in the drone to detect and hover above the Wireless Power Transfer device which got receiving and transmitting station can be use with deep learning and sensor fusion techniques for more reliable flight operations. This thesis explores the use of dynamic wireless power to transfer energy using novel rotating WPT charging technique to the UAV with improved range, endurance, and average speed by giving extra hours in the air. The hypothesis that was created has a broad application beyond UAVs. The drone autonomous charging was mostly done by detecting a rotating WPT receiver connected to main power outlet that served as a recharging platform using deep neural vision capabilities. It was the purpose of the thesis to provide an alternative to traditional self-charging systems that relies purely on static WPT method and requires little distance between the vehicle and receiver. When the UAV camera detect the WPT receiving station, it will try to align and hover using onboard sensors for best power transfer efficiency. Since this strategy relied on traditional automatic drone landing technique, but the target is rotating all the time which needs smart approaches like deep learning and sensor fusion. The simulation environment was created and tested using robot operating system on a Linux operating system using a model of the custom-made drone. Experiments on the charging of the drone confirmed that the intelligent dynamic wireless power transfer (DWPT) method worked successfully while flying on air

Spatio-temporal patterns act as computational mechanisms governing emergent behavior in robotic swarms

Our goal is to control a robotic swarm without removing its swarm-like nature. In other words, we aim to intrinsically control a robotic swarm emergent behavior. Past attempts at governing robotic swarms or their self-coordinating emergent behavior, has proven ineffective, largely due to the swarm's inherent randomness (making it difficult to predict) and utter simplicity (they lack a leader, any kind of centralized control, long-range communication, global knowledge, complex internal models and only operate on a couple of basic, reactive rules). The main problem is that emergent phenomena itself is not fully understood, despite being at the forefront of current research. Research into 1D and 2D Cellular Automata has uncovered a hidden computational layer which bridges the micro-macro gap (i.e., how individual behaviors at the micro-level influence the global behaviors on the macro-level). We hypothesize that there also lie embedded computational mechanisms at the heart of a robotic swarm's emergent behavior. To test this theory, we proceeded to simulate robotic swarms (represented as both particles and dynamic networks) and then designed local rules to induce various types of intelligent, emergent behaviors (as well as designing genetic algorithms to evolve robotic swarms with emergent behaviors). Finally, we analysed these robotic swarms and successfully confirmed our hypothesis; analyzing their developments and interactions over time revealed various forms of embedded spatiotemporal patterns which store, propagate and parallel process information across the swarm according to some internal, collision-based logic (solving the mystery of how simple robots are able to self-coordinate and allow global behaviors to emerge across the swarm)

Body swarm interface (BOSI) : controlling robotic swarms using human bio-signals

Traditionally robots are controlled using devices like joysticks, keyboards, mice and other similar human computer interface (HCI) devices. Although this approach is effective and practical for some cases, it is restrictive only to healthy individuals without disabilities, and it also requires the user to master the device before its usage. It becomes complicated and non-intuitive when multiple robots need to be controlled simultaneously with these traditional devices, as in the case of Human Swarm Interfaces (HSI). This work presents a novel concept of using human bio-signals to control swarms of robots. With this concept there are two major advantages: Firstly, it gives amputees and people with certain disabilities the ability to control robotic swarms, which has previously not been possible. Secondly, it also gives the user a more intuitive interface to control swarms of robots by using gestures, thoughts, and eye movement. We measure different bio-signals from the human body including Electroencephalography (EEG), Electromyography (EMG), Electrooculography (EOG), using off the shelf products. After minimal signal processing, we then decode the intended control action using machine learning techniques like Hidden Markov Models (HMM) and K-Nearest Neighbors (K-NN). We employ formation controllers based on distance and displacement to control the shape and motion of the robotic swarm. Comparison for ground truth for thoughts and gesture classifications are done, and the resulting pipelines are evaluated with both simulations and hardware experiments with swarms of ground robots and aerial vehicles

Wireless Sensor System for Recycling

The motivation of this thesis was to research and design a prototype model of a wireless sensor network application, to be used as an automated detection infrastructure in recycling environment. The initial idea was to measure the level of the surface in a recycling container and transmit the information through a wireless communication system. The prototype is an initial step for recycling companies for building an automated detection network. Background of the research strongly supports the accomplished prototype. Study includes description of wireless environment with its problems and challenges. It proceeds with consideration of suitable wireless standards and considers most convenient sensor methods for recycling environment. Eventually document presents the prototype combining the studied entities. As a result, the prototype has two main operating parts: the wireless communication network and sensors. The network was realized with ZigBee standard by using two radio chips as communication nodes. Second communication node is attached to a recycling container and combined with two ultrasound sensors. This node includes a soft-ware algorithm, which is polling the state of the sensors regularly and deciding if the container is full. The node proceeds to transmission of the information to other communication node. This node is connected to computer and will transmit the information to be used by the recycling organization.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format