Thesis (M. S.)--Mechanical Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Book, Wayne; Committee Member: Lipkin, Harvey; Committee Member: Paredis, Christiaan

Most of work on motion of mobile robots is to generate plans for avoiding obstacles or perform some meaningful and useful actions. In modern robot theatres and entertainment robots the motions of the robot are scripted and thus the performance or behavior of the robot is always the same. In this work we want to propose a new approach to robot motion generation. We want our robot to behave more like real people. People do not move in mechanical way like robots. When a human is supposed to execute some motion, these motions are similar to one another but always slightly or not so slightly different. We want to reproduce this property based on the introduced by us new concept of probabilistic regular expression, a method to describe sets of interrelated similar actions instead of single actions. Our goal is not only to create motions for humanoid robots that will look more naturally and less mechanically, but also to program robots that will combine basic movements from certain library in many different and partially random ways. While the basic motions were created ahead of time, their combinations are specified in our new language. Although now our method is only for motions and does not take inputs from sensors into account, in future the language can be extended to input/output sequences, thus the robot will be able to adapt the motion in different ways, to some sets of sequences of input stimuli. The inputs will come from sensors, possibly attached to limbs of controlling humans from whom the patterns of motion will be acquired.

Lately, personal and entertainment robotics are becoming more and more common. In this thesis, the application of entertainment robots in the context of a Robot Theatre is studied. Specifically, the thesis focuses on the synthesis of expressive movements or animations for the robot performers (Robot Actors). The novel paradigm emerged from computer animation is to represent the motion data as a set of signals. Thus, preprogrammed motion data can be quickly modified using common signal processing techniques such as multiresolution filtering and spectral analysis. However, manual adjustments of the filtering and spectral methods parameters, and good artistic skills are still required to obtain the desired expressions in the resulting animation. Music contains timing, timbre and rhythm information which humans can translate into affect, and express the affect through movement dynamics, such as in dancing. Music data is then assumed to contain affective information which can be expressed in the movements of a robot. In this thesis, music data is used as input signal to generate motion data (Dance) and to modify a sequence of pre-programmed motion data (Scenario) for a custom-made Lynxmotion robot and a KHR-1 robot, respectively. The music data in MIDI format is parsed for timing and melodic information, which are then mapped to joint angle values. Surveys were done to validate the usefulness and contribution of music signals to add expressiveness to the movements of a robot for the Robot Theatre application.

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering in the Control Research Group School of Electrical and Information Engineering, Johannesburg, 2017 / In this research, we observed a torque-related limitation in the swing-up control of underactuated mechanical systems which had been integrated with viscous damping in the unactuated joint. The objective of this research project was thus to develop a practical work-around solution to this limitation. The nth order underactuated robotic system is represented in this research as a collection of compounded pendulums with n-1 actuators placed at each joint with the exception of the first joint. This system is referred to as the PAn-1 robot (Passive first joint, followed by n-1 Active joints), with the Acrobot (PA1 robot) and the PAA robot (or PA2 robot) being among the most well-known examples. A number of friction models exist in literature, which include, and are not exclusive to, the Coulomb and the Stribeck effect models, but the viscous damping model was selected for this research since it is more extensively covered in existing literature. The effectiveness of swing-up control using Lyapunov’s direct method when applied on the undamped PAn-1 robot has been vigorously demonstrated in existing literature, but there is no literature that discusses the swing-up control of viscously damped systems. We show, however, that the application of satisfactory swing-up control using Lyapunov’s direct method is constrained to underactuated systems that are either undamped or actively damped (viscous damping integrated into the actuated joints only). The violation of this constraint results in the derivation of a torque expression that cannot be solved for (invertibility problem, for systems described by n > 2) or a torque expression which contains a conditional singularity (singularity problem, for systems with n = 2). This constraint is formally summarised as the matched damping condition, and highlights a clear limitation in the Lyapunov-related swing-up control of underactuated mechanical systems. This condition has significant implications on the practical realisation of the swing-up control of underactuated mechanical systems, which justifies the investigation into the possibility of a work-around. We thus show that the limitation highlighted by the matched damping condition can be overcome through the implementation of the partial feedback linearisation (PFL) technique. Two key contributions are generated from this research as a result, which iii include the gain selection criterion (for Traditional Collocated PFL), and the convergence algorithm (for noncollocated PFL). The gain selection criterion is an analytical solution that is composed of a set of inequalities that map out a geometric region of appropriate gains in the swing-up gain space. Selecting a gain combination within this region will ensure that the fully-pendent equilibrium point (FPEP) is unstable, which is a necessary condition for swing-up control when the system is initialised near the FPEP. The convergence algorithm is an experimental solution that, once executed, will provide information about the distal pendulum’s angular initial condition that is required to swing-up a robot with a particular angular initial condition for the proximal pendulum, along with the minimum gain that is required to execute the swing-up control in this particular configuration. Significant future contributions on this topic may result from the inclusion of more complex friction models. Additionally, the degree of actuation of the system may be reduced through the implementation of energy storing components, such as torsional springs, at the joint. In summary, we present two contributions in the form of the gain selection criterion and the convergence algorithm which accommodate the circumnavigation of the limitation formalised as the matched damping condition. This condition pertains to the Lyapunov-related swing-up control of underactuated mechanical systems that have been integrated with viscous damping in the unactuated joint. / CK2018

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This dissertation demonstrates that effective control of autonomous mobile robots in real-world environments can be achieved by combining reactive and deliberative components into an integrated architecture. The reactive component allows the robot to respond to contingencies in real time. Deliberation allows the robot to make effective predictions about the world. By using different computational mechanisms for the reactive and deliberative components, much existing deliberative technology can be effectively incorporated into a mobile robot control system. The dissertation describes the design and implementation of a reactive control system for an autonomous mobile robot which is explicitly designed to interface to a deliberative component A programming language called ALF A is developed to program this system. The design of a control architecture which incorporates this reactive system is also described. The architecture is heterogeneous and asynchronous, that is, it consists of components which are structured differently from one another, and which operate in parallel. This prevents slow deliberative computations from adversely affecting the response time of the overall system. The architecture produces behavior which is reliable and goal-directed, yet reactive to contingencies, in the face of noise, limited computational resources, and an unpredictable environment. The system described in this dissertation has been used to control three real robots and a simulated robot performing a variety of tasks in real-world and simulated real-world environments. A general design methodology based upon bottom-up hierarchical decomposition is demonstrated. The methodology is based on the principle of cognizant failure, that is, that low-level activities should be designed in a way as to detect failures and state transitions at high levels of abstraction. Furthermore, the results of deliberative computations should be used to guide the robot's actions, but not to control those actions directly. / Ph. D.

An algorithm for generating communicative, human-like motion for social humanoid robots was developed. Anticipation, exaggeration, and secondary motion were demonstrated as examples of communication. Spatiotemporal correspondence was presented as a metric for human-like motion, and the metric was used to both synthesize and evaluate motion. An algorithm for generating an infinite number of variants from a single exemplar was established to avoid repetitive motion. The algorithm was made task-aware by including the functionality of satisfying constraints. User studies were performed with the algorithm using human participants. Results showed that communicative, human-like motion can be harnessed to direct partner attention and communicate state information. Furthermore, communicative, human-like motion for social robots produced by the algorithm allows humans partners to feel more engaged in the interaction, recognize motion earlier, label intent sooner, and remember interaction details more accurately.

Thesis (M. Tech.) -- Central University of Technology, Free State, 2009 / Automated Guided Vehicles (AGVs) have many different design specifications, although they all have certain design features in common, for instance they are designed to follow predetermined paths, and they need to be aware of their surroundings and changes to their surroundings. They are designed to house sensors for navigation and obstacle avoidance. In this study an AGV platform was developed by modifying an electric wheelchair. A serial port interface was developed between a computer and the control unit of the electric wheelchair, which enables the computer to control the movements of the platform. Different sensors were investigated to determine which would be best suited and most effective to avoid collisions. The sensors chosen were mounted on the AGV and a programme was developed to enable the sensors to assist in avoiding obstacles. An imaging device as an additional sensor system for the AGV was investigated. The image produced by a camera and dome mirror was processed into a panoramic image representing an entire 360o view of the AGV‟s surroundings. The reason for this part of the research was to enable the user to make corrections to the AGV‟s path if it became stuck along the track it was following. The entire system was also made completely wireless to improve the flexibility of the AGV‟s applications.

Thesis (M.Tech.) - Central University of Technology, Free State, 2007 / The latest technological trend worldwide, is automation. Reducing human labour and introducing robots to do the work is a pure business decision. The reason for automating a plant can be some, or all, of the following: Improve productivity Reduce labour and equipment costs Reduce product damage System reliability can be monitored Improves plant safety When the automation process is started, Automatic Guided Vehicles (AGVs) will be one of the first commodities that can be used. The reason for this is that they are so versatile. They can be programmed to follow specific paths when moving material from one point to another and the biggest advantage of all is that they can operate for twenty four hours a day. Automatic Guided Vehicles are developed for many different applications and therefore many different types of AGVs are available. All AGVs are equipped with sensors so that they are able to “see” what is happening around them. Since the AGV must be able to function without any human help or control, it must be able to navigate through the work environment. In this study a remote control car was converted to an AGV and thorough research was done on the different types of sensors that can be used to make the AGV more intelligent when it comes to navigating in an unknown environment.

Thesis (M.Tech.) - Central University of Technology, Free State, 2006 / The ultimate goal regarding this research was to make an intelligent learning machine, thus a new method had to be developed. This was to be made possible by creating a programme that generates another programme. By constantly changing the generated programme to improve itself, the machines are given the ability to adapt to there surroundings and, thus, learn from experience. This generated programme had to perform a specific task. For this experiment the programme was generated for a simulated PIC microcontroller aboard a simulated robot. The goal was to get the robot as close to a specific position inside a simulated maze as possible. The robot therefore had to show the ability to avoid obstacles, although only the distance to the destination was given as an indication of how well the generated programme was performing. The programme performed experiments by randomly changing a number of instructions in the current generated programme. The generated programme was evaluated by simulating the reactions of the robot. If the change to the generated programme resulted in getting the robot closer to the destination, then the changed generated programme was kept for future use. If the change resulted in a less desired reaction, then the newly generated programme was removed and the unchanged programme was kept for future use. This process was repeated for a total of one hundred thousand times before the generated program was considered valid. Because there was a very slim chance that the instruction chosen will be advantageous to the programme, it will take many changes to get the desired instruction and, thus, the desired result. After each change an evaluation was made through simulation. The amount of necessary changes to the programme is greatly reduced by giving seemingly desirable instructions a higher chance of being chosen than the other seemingly unsatisfactory instructions. Due to the extensive use of the random function in this experiment, the results differ from one another. To overcome this barrier, many individual programmes had to be generated by simulating and changing an instruction in the generated programme a hundred thousand times. This method was compared against Genetic Algorithms, which were used to generate a programme for the same simulated robot. The new method made the robot adapt much faster to its surroundings than the Genetic Algorithms. A physical robot, similar to the virtual one, was build to prove that the programmes generated could be used on a physical robot. There were quite a number of differences between the generated programmes and the way in which a human would generally construct the programme. Therefore, this method not only gives programmers a new perspective, but could also possibly do what human programmers have not been able to achieve in the past.