422 research outputs found
Mobile robot transportation in laboratory automation
In this dissertation a new mobile robot transportation system is developed for the modern laboratory automation to connect the distributed automated systems and workbenches. In the system, a series of scientific and technical robot indoor issues are presented and solved, including the multiple robot control strategy, the indoor transportation path planning, the hybrid robot indoor localization, the recharging optimization, the robot-automated door interface, the robot blind arm grasping & placing, etc. The experiments show the proposed system and methods are effective and efficient
CHARMIE: a collaborative healthcare and home service and assistant robot for elderly care
The global population is ageing at an unprecedented rate. With changes in life expectancy across the world, three major issues arise: an increasing proportion of senior citizens; cognitive and physical problems progressively affecting the elderly; and a growing number of single-person households. The available data proves the ever-increasing necessity for efficient elderly care solutions such as healthcare service and assistive robots. Additionally, such robotic solutions provide safe healthcare assistance in public health emergencies such as the SARS-CoV-2 virus (COVID-19). CHARMIE is an anthropomorphic collaborative healthcare and domestic assistant robot capable of performing generic service tasks in non-standardised healthcare and domestic environment settings. The combination of its hardware and software solutions demonstrates map building and self-localisation, safe navigation through dynamic obstacle detection and avoidance, different human-robot interaction systems, speech and hearing, pose/gesture estimation and household object manipulation. Moreover, CHARMIE performs end-to-end chores in nursing homes, domestic houses, and healthcare facilities. Some examples of these chores are to help users transport items, fall detection, tidying up rooms, user following, and set up a table. The robot can perform a wide range of chores, either independently or collaboratively. CHARMIE provides a generic robotic solution such that older people can live longer, more independent, and healthier lives.This work has been supported by FCTāFundaĆ§Ć£o para a CiĆŖncia e Tecnologia within the
R&D Units Project Scope: UIDB/00319/2020. The author T.R. received funding through a doctoral
scholarship from the Portuguese Foundation for Science and Technology (FundaĆ§Ć£o para a CiĆŖncia
e a Tecnologia) [grant number SFRH/BD/06944/2020], with funds from the Portuguese Ministry
of Science, Technology and Higher Education and the European Social Fund through the Programa
Operacional do Capital Humano (POCH). The author F.G. received funding through a doctoral
scholarship from the Portuguese Foundation for Science and Technology (FundaĆ§Ć£o para a CiĆŖncia
e a Tecnologia) [grant number SFRH/BD/145993/2019], with funds from the Portuguese Ministry
of Science, Technology and Higher Education and the European Social Fund through the Programa
Operacional do Capital Humano (POCH)
Specialization of Perceptual Processes
In this report, I discuss the use of vision to support concrete, everyday activity. I will argue that a variety of interesting tasks can be solved using simple and inexpensive vision systems. I will provide a number of working examples in the form of a state-of-the-art mobile robot, Polly, which uses vision to give primitive tours of the seventh floor of the MIT AI Laboratory. By current standards, the robot has a broad behavioral repertoire and is both simple and inexpensive (the complete robot was built for less than $20,000 using commercial board-level components). The approach I will use will be to treat the structure of the agent's activity---its task and environment---as positive resources for the vision system designer. By performing a careful analysis of task and environment, the designer can determine a broad space of mechanisms which can perform the desired activity. My principal thesis is that for a broad range of activities, the space of applicable mechanisms will be broad enough to include a number mechanisms which are simple and economical. The simplest mechanisms that solve a given problem will typically be quite specialized to that problem. One thus worries that building simple vision systems will be require a great deal of {it ad-hoc} engineering that cannot be transferred to other problems. My second thesis is that specialized systems can be analyzed and understood in a principled manner, one that allows general lessons to be extracted from specialized systems. I will present a general approach to analyzing specialization through the use of transformations that provably improve performance. By demonstrating a sequence of transformations that derive a specialized system from a more general one, we can summarize the specialization of the former in a compact form that makes explicit the additional assumptions that it makes about its environment. The summary can be used to predict the performance of the system in novel environments. Individual transformations can be recycled in the design of future systems
Robots learn to behave: improving human-robot collaboration in flexible manufacturing applications
L'abstract ĆØ presente nell'allegato / the abstract is in the attachmen
VSLAM and Navigation System of Unmanned Ground Vehicle Based on RGB-D Camera
In this thesis, ROS (Robot Operating System) is used as the software platform and a simple unmanned ground vehicle that is designed and constructed by myself is used as the hardware platform. The most critical issues in the navigation technology of unmanned ground vehicles in unknown environments -SLAM (Simultaneous Localization and Mapping) and autonomous navigation technology are studied. Through the analysis of the principle and structure of visual SLAM, a visual simultaneous localization and mapping algorithm is build. Moreover, accelerate the visual SLAM algorithm through hardware replacement and software algorithm optimization. RealSense D435 is used as the camera of the VSLAM sensor. The algorithm extracts the features from the data of depth camera and calculates the odometry information of the unmanned vehicle through the features matching of the adjacent image. Then update the vehicleās location and map data using the odometry information.
Under the condition that the visual SLAM algorithm works normally, this thesis also uses the 3D map generated to derive the real-time 2D projection map. So as to apply it to the navigation algorithm. Then this thesis realize autonomous navigation and avoids the obstacle function of unmanned vehicle by controlling the driving speed and direction of the vehicle through the navigation algorithm using the 2D projection map. Unmanned ground vehicle path planning is mainly two parts: local path planning and global path planning. Global path planning is mainly used to plan the optimal path to the destination. Local path planning is mainly used to control the speed and direction of the UGV. This thesis analyzes and compares Dijkstraās algorithm and A* algorithm. Considering the compatible to ROS, Dijkstraās algorithm is finally used as the global path-planning algorithm. DWA (Dynamic Window Approach) algorithm is used as Local path planning. Under the control of the Dijkstraās algorithm and the DWA algorithm, unmanned ground vehicles can automatically plan the optimal path to the target point and avoid obstacles. This thesis also designed and constructed a simple unmanned ground vehicle as an experimental platform and design a simple control method basing on differential wheeled unmanned ground vehicle and finally realized the autonomous navigation of unmanned ground vehicles and the function of avoiding obstacles through visual SLAM algorithm and autonomous navigation algorithm.
Finally, the main work and deficiencies of this thesis are summarized. And the prospects and difficulties of the research field of unmanned ground vehicles are presented
Cartographie, localisation et planification simultaneĢes āen ligneā, aĢ long terme et aĢ grande eĢchelle pour robot mobile
Pour eĢtre en mesure de naviguer dans des endroits inconnus et non structureĢs, un robot doit pouvoir cartographier lāenvironnement afin de sāy localiser. Ce probleĢme est connu sous le nom de cartographie et localisation simultaneĢes (ou SLAM pour Simultaneous Localization and Mapping). Une fois la carte de lāenvironnement creĢeĢe, des taĢches requeĢrant un deĢplacement dāun endroit connu aĢ un autre peuvent ainsi eĢtre planifieĢes. La charge de calcul du SLAM est deĢpendante de la grandeur de la carte. Un robot a une puissance de calcul embarqueĢe limiteĢe pour arriver aĢ traiter lāinformation āen ligneā, cāest-aĢ-dire aĢ bord du robot avec un temps de traitement des donneĢes moins long que le temps dāacquisition des donneĢes ou le temps maximal permis de mise aĢ jour de la carte. La navigation du robot tout en faisant le SLAM est donc limiteĢe par la taille de lāenvironnement aĢ cartographier.
Pour reĢsoudre cette probleĢmatique, lāobjectif est de deĢvelopper un algorithme de SPLAM (Simultaneous Planning Localization and Mapping) permettant la navigation peu importe la taille de lāenvironment. Pour geĢrer efficacement la charge de calcul de cet algorithme, la meĢmoire du robot est diviseĢe en une meĢmoire de travail et une meĢmoire aĢ long terme. Lorsque la contrainte de traitement āen ligneā est atteinte, les endroits vus les moins souvent et qui ne sont pas utiles pour la navigation sont transfeĢreĢes de la meĢmoire de travail aĢ la meĢmoire aĢ long terme. Les endroits transfeĢreĢs dans la meĢmoire aĢ long terme ne sont plus utiliseĢs pour la navigation. Cependant, ces endroits transfeĢreĢs peuvent eĢtre reĢcupeĢreĢes de la meĢmoire aĢ long terme aĢ la meĢmoire de travail lorsque le le robot sāapproche dāun endroit voisin encore dans la meĢmoire de travail. Le robot peut ainsi se rappeler increĢmentalement dāune partie de lāenvironment a priori oublieĢe afin de pouvoir sāy localiser pour le suivi de trajectoire.
Lāalgorithme, nommeĢ RTAB-Map, a eĢteĢ testeĢ sur le robot AZIMUT-3 dans une premieĢre expeĢrience de cartographie sur cinq sessions indeĢpendantes, afin dāeĢvaluer la capaciteĢ du systeĢme aĢ fusionner plusieurs cartes āen ligneā. La seconde expeĢrience, avec le meĢme robot utiliseĢ lors de onze sessions totalisant 8 heures de deĢplacement, a permis dāeĢvaluer la capaciteĢ du robot de naviguer de facĢ§on autonome tout en faisant du SLAM et planifier des trajectoires continuellement sur une longue peĢriode en respectant la contrainte de traitement āen ligneā . Enfin, RTAB-Map est compareĢ aĢ dāautres systeĢmes de SLAM sur quatre ensembles de donneĢes populaires pour des applications de voiture autonome (KITTI), balayage aĢ la main avec une cameĢra RGB-D (TUM RGB-D), de drone (EuRoC) et de navigation inteĢrieur avec un robot PR2 (MIT Stata Center).
Les reĢsultats montrent que RTAB-Map peut eĢtre utiliseĢ sur de longue peĢriode de temps en navigation autonome tout en respectant la contrainte de traitement āen ligneā et avec une qualiteĢ de carte comparable aux approches de lāeĢtat de lāart en SLAM visuel et avec teĢleĢmeĢtre laser. ll en reĢsulte dāun logiciel libre deĢployeĢ dans une multitude dāapplications allant des robots mobiles inteĢrieurs peu couĢteux aux voitures autonomes, en passant par les drones et la modeĢlisation 3D de lāinteĢrieur dāune maison
3D multi-robot patrolling with a two-level coordination strategy
Teams of UGVs patrolling harsh and complex 3D environments can experience interference and spatial conflicts with one another. Neglecting the occurrence of these events crucially hinders both soundness and reliability of a patrolling process. This work presents a distributed multi-robot patrolling technique, which uses a two-level coordination strategy to minimize and explicitly manage the occurrence of conflicts and interference. The first level guides the agents to single out exclusive target nodes on a topological map. This target selection relies on a shared idleness representation and a coordination mechanism preventing topological conflicts. The second level hosts coordination strategies based on a metric representation of space and is supported by a 3D SLAM system. Here, each robot path planner negotiates spatial conflicts by applying a multi-robot traversability function. Continuous interactions between these two levels ensure coordination and conflicts resolution. Both simulations and real-world experiments are presented to validate the performances of the proposed patrolling strategy in 3D environments. Results show this is a promising solution for managing spatial conflicts and preventing deadlocks
Development of new intelligent autonomous robotic assistant for hospitals
Continuous technological development in modern societies has increased the quality of life and average life-span of people. This imposes an extra burden on the current healthcare infrastructure, which also creates the opportunity for developing new, autonomous, assistive robots to help alleviate this extra workload.
The research question explored the extent to which a prototypical robotic platform can be created and how it may be implemented in a hospital environment with the aim to assist the hospital staff with daily tasks, such as guiding patients and visitors, following patients to ensure safety, and making deliveries to and from rooms and workstations.
In terms of major contributions, this thesis outlines five domains of the development of an actual robotic assistant prototype. Firstly, a comprehensive schematic design is presented in which mechanical, electrical, motor control and kinematics solutions have been examined in detail. Next, a new method has been proposed for assessing the intrinsic properties of different flooring-types using machine learning to classify mechanical vibrations. Thirdly, the technical challenge of enabling the robot to simultaneously map and localise itself in a dynamic environment has been addressed, whereby leg detection is introduced to ensure that, whilst mapping, the robot is able to distinguish between people and the background. The fourth contribution is geometric collision prediction into stabilised dynamic navigation methods, thus optimising the navigation ability to update real-time path planning in a dynamic environment. Lastly, the problem of detecting gaze at long distances has been addressed by means of a new eye-tracking hardware solution which combines infra-red eye tracking and depth sensing.
The research serves both to provide a template for the development of comprehensive mobile assistive-robot solutions, and to address some of the inherent challenges currently present in introducing autonomous assistive robots in hospital environments.Open Acces
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