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It is becoming increasingly necessary to carry out manual operations in environments which are hazardous to humans - using remote manipulator systems that can extend the operators reach. However, manual dexterity can become severely impaired due to the complex relationship that exists between the operator, the remote manipulator system and the task. Under such circumstances, the introduction of force feedback is considered a desirable feature, and is particularly important when attempting to carry out complex assembly operations. The dynamic interaction in the manmachine system can significantly influence performance, and in the past evaluation has been largely by comparative assessment. In this study, an experimental remote manipulator system, or tele-manipulator system, has been developed which consists of three electrically linked planar manipulator arms, each with three degrees of freedom. An articulated 'master' arm is used to control an identical 'slave' arm, and independently, a second kinematically and dynamically dissimilar slave arm. Fully resolved Generalized Control has been demonstrated using a high speed computer to carry out the necessary position and force transformations between dissimilar master and slave arms in realtime. Simulation of a one degree of freedom master-slave system has also been carried out, which includes a simple model of the human operator and a task based upon a rigid stop. The results show good agreement with parallel experimental tests, and have provided a firm foundation for developing a fully resolved position/position control scheme, and a unique way of backdriving the master arm. Preliminary tests were based on a peg-in-hole transfer task, and have identified the effect on performance of force reflection ratio. More recently a novel crank-turning task has been developed to investigate the interaction of system parameters on overall performance. The results obtained from these experimental studies, backed up by simulation, demonstrate the potential of computer augmented control of remote manipulator systems. The directions for future work include development of real-time control of tele-robotic systems and research into the overall man-machine interaction.

Telemanipulators allow a user to interact with a potentially dangerous environment remotely. Deploying a robot arm from a UAV would allow an operator to reach farther and quicker than he or she would with a ground robotics system alone. This thesis will discuss the design and fabrication of a compact, light, 3 degree of freedom robot arm using common off the shelf products and machined components that in combination can pick up half pound samples and has a reach of 260 mm. Also addressed is making the telemanipulator interface easier to use. One of the challenges in using a robot arm with a single camera in a beyond line-of-sight scenario is the difficulty of interacting with the environment because of a loss of depth information. This lack of information can be remedied with additional sensors. Once depth to an object of interest is known, the sampler can automatically pick up objects of interest. The manipulator arm will be used in conjunction with systems developed by the Unmanned Systems Laboratory at Virginia Tech. This group is developing a unmanned ground vehicle to be carried in the payload pod of a unmanned aerial vehicle. The robot's ultimate objective is to collect shrapnel and bomb material from potentially dangerous environments. / Master of Science

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In urban conditions architecture often loses a connection with the surrounding context and viewers through inappropriate scale, design orientation and the misuse of light during the day and night. In areas of density, perception is everything. This exploration seeks to express architecture as a language of light and transparency by emphasizing a long linear connection with the ground plane and surrounding city. This creates horizontal bands of space that emit and receive various forms of light. The goal of this thesis is to portray itself as a glowing beacon of attraction while simultaneously displaying its inner workings. / Master of Architecture

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Existing robotic arms have limited or no ability to avoid collisions with their environment due mainly to the lack of a suitable sensing system. A collision avoidance capability should be incorporated into every robot so that injuries to people and damage to equipment from collisions are prevented. Important applications that could benefit from robot collision avoidance include: manufacturing, robot-assisted surgery, robotic handling of hazardous waste, and personal robots. Creating a full-coverage, fast, reliable and cost effective sensing system for sensor-based robotic arm collision avoidance is a challenging problem. Capacitive sensors were selected based on their promising potential. Capacitive sensors have the limitations of nonlinearity and being influenced by the environment. In this thesis, their sensing behaviour, and solutions to these limitations, were investigated. A forward model predicts the capacitance for a given electrode geometry. The conventional method, Method of Moments (MoM) and Finite Element Method (FEM) were investigated and compared. The MoM demonstrated that the fringing electric field ignored by the conventional forward model is significant for the robotic arm application due to the relatively large ratio of electrode gap to electrode area. Two forward modeling cases were simulated by writing macro code for a commercial FEM package. The first consisted of two parallel cylindrical robotic arms. The second consisted of two cylindrical shell electrodes wrapped around a pair of robot links that rotated relative to each other. The results for this case were compared with experimental results. The FEM results were a poor predictor of the experimental results. The failure of the FEM model to include the true environmental conditions (e.g. air humidity and surrounding electric fields) is the most likely cause of its inaccuracy. An inverse capacitance model outputs the electrode geometry for a given capacitance. In this research the desired geometric output was the seven robot link pose variables, (x, y, z, q_x, q_y, q_z, q_0), describing the position and the orientation of the link of a robotic arm. A Cerebellar Model Articulation Controller (CMAC) neural network was chosen for the inverse modeling based its ability to model nonlinear behaviour and its efficiency. One CMAC network was trained for each pose variable. The sensor was built using capacitance sensing circuit and a multiplexor board with the potential for 16 by 16 electrode combinations. Note that an n by n combination produces n^2 separate capacitance values. For the inverse modeling experiments, four aluminum foil electrodes were mounted on a CRS-F3 robotic arm and four aluminum foil electrodes were placed on a wooden box used to simulate a second stationary robotic arm. A pair of reference electrodes was mounted on the back of the CRS-F3 arm. This reference measurement was used to normalize the measured capacitances in order to minimize environmental effects. The normalized capacitance data were used to train and test the CMAC neural networks. The CMAC learning factors were dynamically changed to reduce the training errors. A new fuzzy logic approach was developed that allowed the range of the CMAC input data to be increased without significantly increasing the training error. After evaluating eleven combinations of electrodes, it was determined that only the 3 by 3 and 4 by 4 combinations converged with small training errors. Three methods were used to analyze the CMAC testing errors: comparison plots, error plots and error metrics. Over a 15 cm range, pose variable y had maximum absolute errors of 2.1 mm for the 4 by 4 electrode combination and 7.2 mm for the 3 by 3 electrode combination. For the 4 by 4 combination the maximum relative errors were less than 3% for the x, y, and z variables, and less than 15% for the quaternion variables. For the 3 by 3 combination, these values increased to 13% and 20%, respectively. The larger relative errors for the quaternion variables were due to their smaller ranges of variation. Using the same hardware, a simple collision avoidance system was implemented using one pair of electrodes to detect the potential collision between a robotic arm moving in the vertical plane and a second stationary robot. The robot was shown to successfully avoid the potential collision and then continue its motion. / Thesis / Master of Applied Science (MASc)

Robot manipulators are getting more and more attention nowadays. This is due to their high precision and the speed they provide while executing their tasks. The desires for such high standards are increasing exponentially due to the extended workspace that manipulators provide. Therefore, a safe controller is needed to make it possible for the robot to work alongside people considering the safety precautions. These safety preconditions are widely spread, even when the needs for better human-friendly robots are rising. This thesis will introduce and explain a way to model a 6-axis robot by using its dynamical properties as well as the development of a joint space inverse dynamic controller. The controller will be tested in various different ways. Firstly by adding noise to the measured data. Then testing the robustness of the control model, while the simulated model includes properties different from those used for the controller itself. The different properties would for example be payloads and the inertia of the links. Thereafter, evaluating the precision of a followed path that is given by an operational space trajectory. The outcome of these experiments show promising results. The results show that the controller is able to manage a noise in both the joint angle and joint velocity. It also shows that an error in the payload data will give a small error in the joint angles, sequentially that gives an acceptable error for the end-effector in the operational space. Furthermore, the controller manages to keep the maximum errorin the joint angle low, while it is following a trajectory in the operational space.

This thesis project investigated whether or not the use of an embedded system could help blackjack players to improve their game. This was done by designing and building a robot, that plays blackjack according to a card counting strategy. A robot prototype was built successfully, using a USB-camera to detect the cards and servo-motors to signal its playing decisions via hand gestures. Tests showed that the robot has a 1.4% edge over the house on average. However, due to high variance in the outcomes, the positive return found is non-significant. Recommendations of future work is proposed, including how both players and casinos can benefit from this project. / Detta examensarbete undersökte om ett inbyggt system kan hjälpa blackjackspelare att förbättra sitt spel. Detta gjordes genom att konstruera och bygga en robot, som spelar blackjack enligt en korträkningsstrategi. En robotprototyp byggdes med hjälp av en USB-kamera för att läsa av spelkorten, och servomotorer för att signalera spelbeslut genom handgester. Tester visade att roboten har i genomsnitt 1.4% fördel över huset. Dock är denna positiva avkastning icke-signifikant på grund av hög varians i utfallen. Rekommendationer om framtida arbete föreslås, som inkluderar hur både spelare och casinon kan dra nytta av detta projekt.

Recycling is becoming more crucial due to the fast pace of consumerism. This thesis explores how well a robot arm, with three degrees of freedom, can be implemented to give an autonomous recycling process. After the prototyping phase it was found that a cylindrical robot arm was best suited for the project. Computer vision in addition with machine learning is used for sorting and detecting objects. The end effector is a suction cup, connected to a plastic 60-milliliter syringe. Negative pressure is created by pulling and pushing a lead screw connected to a stepper motor. The accuracy of the ML-model, the robot’s movement andmax weight are evaluated. The ML-model is trained to detect four classes; plastic, metal, paper, and glass. The thesis found that the ML-model could classify plastic the most sufficient and paper the least. The robot arm’s movement had an average error of 0.54 cm and the maximum weight was 900 grams. For future development it would be interesting to compare a range of different suction cups, to see how the material, diameter, and depth would affect its ability to pick up various objects. Additionally, the model could be enhanced by training it on a larger dataset.