Thesis (Ph. D.) -- California Institute of Technology, 2010. / Title from home page (viewed 03/02/2010). Advisor and committee chair names found in the thesis' metadata record in the digital repository. Includes bibliographical references.

Thesis (Ph.D.) -- University of Texas at Arlington, 2008.

Thesis (M. Phil.)--University of Hong Kong, 2002. / Includes bibliographical references.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references. Also available in electronic version. Access restricted to campus users.

Examensarbetet har utförts på företaget Husqvarna AB vid avdelning Concept & Features electric products (EN-NEP). Uppdraget var att utvärdera en alternativ kollisionsmetod till deras robotgräsklippare. Metoden som utvärderats går ut på att detektera kollision med hjälp av samplad data från en accelerometer samt samplad strömnivå från de bägge drivhjulens motorer. Den metod som används för att detektera kollision på nuvarande robotar fungerar väl men kräver att robotens kaross och chassi rör sig ifrån varandra för att krock skall detekteras. För att kunna reducera antalet komponenter och priset på roboten är andra metoder intressanta att utvärdera för uppdragsgivaren. En algoritm har designats i simulationsmiljö som sedan testats på ”riktigt” genom implementation i en Raspberry Pi som kommunicerar med robotgräsklipparen. Om den implementerade algoritmen detekterat krock på den samplade datan skickas ett meddelande till roboten att utföra sitt inbyggda krockmönster. Resultatet som erhölls var ett fungerande system med stor potential. Med fortsatt arbete skulle metoden kunna bli en framtida ersättare alternativt ett komplement till nuvarande metod.

Recent advancements in control systems, such as the ones used in missile technology in the military or autonomous vehicle development have motivated this study in an attempt to explore various control algorithms and their implementation relevant those applications. Both missile interceptor and autonomous vehicle technology require precise and responsive control system to accurately determine the projectile path of pursuer to strike a moving target or reach a static finish line.The objective of this study is to investigate the performance of several control techniques for a mobile robot to autonomously track and pursue a moving object. Computer model is developed to numerically predict the path taken by the pursuer as it tracks an object moving in regular or random manner. In the computer simulation, the robot's path is calculated using three different techniques: reactive controller, linear estimation, and artificial neural network. Fitness of each method may be determined by evaluating the controller against several factors, such as interception time, steady-state positional error, steady-state time (settling time) and algorithm complexity, listed in decreasing order of importance. A working experimental model is developed to validate the controller selection determined from the computer model simulation. In the experimental setting, the primary inputs to the robot are visual images from cameras. The experiments are carried out with the robot receiving visual inputs from two different perspectives, overhead and frontal vision. Robust image processing technique becomes a topic of significant importance for the system. To manipulate visual images in real-time from raw inputs to comprehensible data, while maintaining fast computational time is a challenge that is addressed in this study. The results from computer simulations show that artificial neural network is a more powerful control algorithm, capable of estimating the object's path more accurately than the other two controllers, resulting in smaller steady-state positional error. The experimental results confirm this conclusion as artificial neural network outperforms the reactive and linear controller by intercepting the object more quickly, i.e. shorter interception time. / text

Η παρούσα εργασία μελετά την εξερεύνηση χώρου από κινούμενα ρομπότ. Πιο συγκεκριμένα, περιοριζόμαστε σε ένα δισδιάστατο χώρο γνωστού μεγέθους, στον οποίο υπάρχουν τυχαία τοποθετημένα εμπόδια. Τα όρια του χώρου είναι εκ των προτέρων γνωστά, ενώ τα εμπόδια είναι ανιχνεύσιμα εφόσον το ρομπότ είναι πλησίον τους. Η μελέτη αφορά σημειακά ρομπότ, τα οποία ξεκινούν από a priori γνωστές συντεταγμένες. Ο χώρος διαμερίζεται σε κελιά και το ρομπότ μπορεί να μεταβεί σε ένα από τα τέσσερα γειτονικά του κελιά. Παράλληλα τα ρομπότ ανταλλάσσουν πληροφορίες μεταξύ τους, αναφορικά με την περιοχή που έχουν ήδη καλύψει. Τελικός στόχος της εργασίας είναι τα ρομπότ, σε συνεργασία μεταξύ τους, να καλύψουν όλα τα κελιά στα οποία είναι διαμοιρασμένος ο χώρος στον ταχύτερο δυνατό χρόνο. / This thesis studies the surveillance problem using mobile robot. We consider an a priori known two-dimensional space, which has randomly placed obstacles. The boundary of the area is known in advance, while the obstacles are detectable, if they are inside the robot's sensing range. The study concerns point-robots, that start from a priori known coordinates. The space is partitioned into cells and the robot can move to one of the four neighboring cells. Furthermore, robots exchange information among themselves regarding the area that is already covered. The ultimate goal of this work is a collaborative scheme for mobile robots in order to survey the area at the smallest possible time.

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Robotic rehabilitation and assessment of the human upper-limb following stroke is currently limited in part by the inability of robots to replicate natural motion. In particular, motion of the shoulder girdle is usually neglected, despite the fact that the shoulder girdle is necessary to stabilize and orient the upper-limb during activities of daily living. Without direct control of the shoulder girdle, it is not possible to monitor or prevent a patient from making compensatory movements, which inhibits functional recovery, nor is there a means to properly regain strength and coordination. The more the robot is able to realistically mimic upper-limb motion, the more able the robot will be to assist with true functional movement training, which gives the patient the best chance of motor recovery. To address this issue, a new adjustable robotic exoskeleton called MEDARM is proposed for rehabilitation and assessment of the shoulder complex. MEDARM provides independent control of six degrees of freedom of the upper-limb: two at the sternoclavicular joint, three at the glenohumeral joint and one at the elbow. A key design feature of the new robot is an innovative curved track mechanism actuated by a cable-drive transmission system. To facilitate a performance evaluation of this new mechanism, a planar version of MEDARM was designed. A full prototype of this planar robot was constructed and several fundamental metrics, including friction, inertia, and compliance, were used to test its mechanical performance. Additionally, the functionality of the robot was examined using preliminary data recorded during a standard reaching task, and by implementing some basic rehabilitation algorithms. This thesis describes the design of MEDARM and its planar counterpart in detail and the performance evaluation of the prototype is presented. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2008-08-13 21:19:14.335

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