Migration from Teleoperation to Autonomy via Modular Sensor and Mobility Bricks

In this thesis, the teleoperated communications of a Remotec ANDROS robot have been reverse engineered. This research has used the information acquired through the reverse engineering process to enhance the teleoperation and add intelligence to the initially automated robot. The main contribution of this thesis is the implementation of the mobility brick paradigm, which enables autonomous operations, using the commercial teleoperated ANDROS platform. The brick paradigm is a generalized architecture for a modular approach to robotics. This architecture and the contribution of this thesis are a paradigm shift from the proprietary commercial models that exist today. The modular system of sensor bricks integrates the transformed mobility platform and defines it as a mobility brick. In the wall following application implemented in this work, the mobile robotic system acquires intelligence using the range sensor brick. This application illustrates a way to alleviate the burden on the human operator and delegate certain tasks to the robot. Wall following is one among several examples of giving a degree of autonomy to an essentially teleoperated robot through the Sensor Brick System. Indeed once the proprietary robot has been altered into a mobility brick; the possibilities for autonomy are numerous and vary with different sensor bricks. The autonomous system implemented is not a fixed-application robot but rather a non-specific autonomy capable platform. Meanwhile the native controller and the computer-interfaced teleoperation are still available when necessary. Rather than trading off by switching from teleoperation to autonomy, this system provides the flexibility to switch between the two at the operator’s command. The contributions of this thesis reside in the reverse engineering of the original robot, its upgrade to a computer-interfaced teleoperated system, the mobility brick paradigm and the addition of autonomy capabilities. The application of a robot autonomously following a wall is subsequently implemented, tested and analyzed in this work. The analysis provides the programmer with information on controlling the robot and launching the autonomous function. The results are conclusive and open up the possibilities for a variety of autonomous applications for mobility platforms using modular sensor bricks

Cybernetic automata: An approach for the realization of economical cognition for multi-robot systems

The multi-agent robotics paradigm has attracted much attention due to the variety of pertinent applications that are well-served by the use of a multiplicity of agents (including space robotics, search and rescue, and mobile sensor networks). The use of this paradigm for most applications, however, demands economical, lightweight agent designs for reasons of longer operational life, lower economic cost, faster and easily-verified designs, etc. An important contributing factor to an agent’s cost is its control architecture. Due to the emergence of novel implementation technologies carrying the promise of economical implementation, we consider the development of a technology-independent specification for computational machinery. To that end, the use of cybernetics toolsets (control and dynamical systems theory) is appropriate, enabling a principled specifi- cation of robotic control architectures in mathematical terms that could be mapped directly to diverse implementation substrates. This dissertation, hence, addresses the problem of developing a technologyindependent specification for lightweight control architectures to enable robotic agents to serve in a multi-agent scheme. We present the principled design of static and dynamical regulators that elicit useful behaviors, and integrate these within an overall architecture for both single and multi-agent control. Since the use of control theory can be limited in unstructured environments, a major focus of the work is on the engineering of emergent behavior. The proposed scheme is highly decentralized, requiring only local sensing and no inter-agent communication. Beyond several simulation-based studies, we provide experimental results for a two-agent system, based on a custom implementation employing field-programmable gate arrays

Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described

Motion Planning

Motion planning is a fundamental function in robotics and numerous intelligent machines. The global concept of planning involves multiple capabilities, such as path generation, dynamic planning, optimization, tracking, and control. This book has organized different planning topics into three general perspectives that are classified by the type of robotic applications. The chapters are a selection of recent developments in a) planning and tracking methods for unmanned aerial vehicles, b) heuristically based methods for navigation planning and routes optimization, and c) control techniques developed for path planning of autonomous wheeled platforms

An Incremental Navigation Localization Methodology for Application to Semi-Autonomous Mobile Robotic Platforms to Assist Individuals Having Severe Motor Disabilities.

In the present work, the author explores the issues surrounding the design and development of an intelligent wheelchair platform incorporating the semi-autonomous system paradigm, to meet the needs of individuals with severe motor disabilities. The author presents a discussion of the problems of navigation that must be solved before any system of this type can be instantiated, and enumerates the general design issues that must be addressed by the designers of systems of this type. This discussion includes reviews of various methodologies that have been proposed as solutions to the problems considered. Next, the author introduces a new navigation method, called Incremental Signature Recognition (ISR), for use by semi-autonomous systems in structured environments. This method is based on the recognition, recording, and tracking of environmental discontinuities: sensor reported anomalies in measured environmental parameters. The author then proposes a robust, redundant, dynamic, self-diagnosing sensing methodology for detecting and compensating for hidden failures of single sensors and sensor idiosyncrasies. This technique is optimized for the detection of spatial discontinuity anomalies. Finally, the author gives details of an effort to realize a prototype ISR based system, along with insights into the various implementation choices made

Interaction and Intelligent Behavior

We introduce basic behaviors as primitives for control and learning in situated, embodied agents interacting in complex domains. We propose methods for selecting, formally specifying, algorithmically implementing, empirically evaluating, and combining behaviors from a basic set. We also introduce a general methodology for automatically constructing higher--level behaviors by learning to select from this set. Based on a formulation of reinforcement learning using conditions, behaviors, and shaped reinforcement, out approach makes behavior selection learnable in noisy, uncertain environments with stochastic dynamics. All described ideas are validated with groups of up to 20 mobile robots performing safe--wandering, following, aggregation, dispersion, homing, flocking, foraging, and learning to forage

Development of a service robot with an open architecture and advanced interface.

Chow Man Kit.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 88-92).Abstracts in English and Chinese.ABSTRACT --- p.i摘要 --- p.iiiACKNOWLEDGEMENTS --- p.vTABLE OF CONTENTS --- p.viLIST OF FIGURES --- p.ixLIST OF TABLES --- p.xiChapter 1. --- INTRODUCTION --- p.1Chapter 1.1 --- Previous Models on Robot Software Architecture --- p.2Chapter 1.1.1 --- SPA --- p.2Chapter 1.1.2 --- Sub sumption Architecture --- p.3Chapter 1.1.3 --- Three Layer Architecture --- p.4Chapter 1.1.4 --- Two Layer Architecture --- p.6Chapter 1.1.5 --- RCS --- p.7Chapter 1.2 --- Motivation and Research Objective --- p.9Chapter 1.2.1 --- Motivation --- p.9Chapter 1.2.2 --- Contribution --- p.10Chapter 1.3 --- Thesis Outline --- p.11Chapter 2. --- STUDY ON ARCHITECTURE --- p.12Chapter 2.1 --- Hierarchy in Architecture --- p.12Chapter 2.1.1 --- Purpose of Hierarchy --- p.12Chapter 2.1.2 --- Suggested Hierarchy --- p.14Chapter 2.1.3 --- Short Summary in Hierarchy --- p.18Chapter 2.2 --- Modularity in Architecture --- p.18Chapter 2.2.1 --- Purpose of Modularity --- p.18Chapter 2.2.2 --- Suggested Modularity --- p.19Chapter 2.3 --- Connectivity in Architecture --- p.20Chapter 2.3.1 --- Purpose of Connectivity --- p.20Chapter 2.3.2 --- Suggested Connectivity --- p.21Chapter 3. --- STUDY ON INTERFACES --- p.23Chapter 3.1 --- Physical Interface --- p.24Chapter 3.2 --- Application Programming Interface (API) --- p.24Chapter 3.3 --- User Interface --- p.27Chapter 4. --- PROSPOSED ROBOT SOFTWARE ARCHITECTURE --- p.29Chapter 5. --- PRACTICAL IMPLEMENTATION --- p.32Chapter 5.1 --- Hardware Implementation --- p.32Chapter 5.1.1 --- Driving Module --- p.33Chapter 5.1.1.1 --- Wheels and motors arrangement --- p.36Chapter 5.1.1.2 --- Kinematics of wheeled mobile robot --- p.37Chapter 5.1.1.3 --- Inverse kinematics of the mobile robot --- p.41Chapter 5.1.1.4 --- Dynamic Controller --- p.44Chapter 5.1.1.5 --- Emergency Stop --- p.52Chapter 5.1.1.6 --- Homing Mechanism for Steering Axis --- p.53Chapter 5.1.2 --- Sensing Module --- p.54Chapter 5.1.2.1 --- Sensing System --- p.55Chapter 5.1.2.2 --- Using Comport as the Data Transmission Medium --- p.55Chapter 5.1.3 --- Power Configuration --- p.56Chapter 5.1.3.1 --- Basic Power Connection --- p.57Chapter 5.1.3.2 --- Design on Power Distribution System --- p.57Chapter 5.2 --- Software Considerations --- p.59Chapter 5.2.1 --- Operating System --- p.59Chapter 5.2.2 --- Parallel Processing --- p.59Chapter 5.3 --- Implementation of Robot Software Architecture --- p.61Chapter 5.3.1 --- Local Terminal Module --- p.62Chapter 5.3.2 --- Navigation Module --- p.62Chapter 5.3.3 --- Sensing Module --- p.64Chapter 5.3.3.1 --- Sensor Data Retrieval --- p.65Chapter 5.3.3.2 --- Error Checking --- p.65Chapter 5.3.3.3 --- Calculating Obstacle Repulsive Vector --- p.67Chapter 5.3.3.4 --- Visualizing Sensor Data --- p.67Chapter 5.3.4 --- Communication Module --- p.68Chapter 5.3.5 --- New idea integrated in Communication Module --- p.70Chapter 5.4 --- Summary --- p.73Chapter 6. --- APPICATION EXAMPLE AND EXPERIMENT --- p.76Chapter 6.1 --- Application Example --- p.77Chapter 6.2 --- Experiment --- p.78Chapter 7. --- CONCLUSIONS AND FUTURE WORKS --- p.81Chapter 7.1 --- Conclusions --- p.81Chapter 7.2 --- Future Works --- p.83APPENDIX --- p.84Chapter A. --- Homing Mechanism for Steering Axis --- p.84Chapter A.1 --- Working Algorithm --- p.84Chapter A.2 --- Hardware Component --- p.85Chapter A.3 --- Circuit Diagram --- p.85Chapter A.4 --- Pin Assignment --- p.85Chapter B. --- Power Specification --- p.86Chapter B.1 --- Power Consumption by PC --- p.86Chapter B.2 --- Hardware Component on Power --- p.87BIBLIOGRAPHY --- p.8

Autonomous Navigation and Mapping using Monocular Low-Resolution Grayscale Vision

Vision has been a powerful tool for navigation of intelligent and man-made systems ever since the cybernetics revolution in the 1970s. There have been two basic approaches to the navigation of computer controlled systems: The self-contained bottom-up development of sensorimotor abilities, namely perception and mobility, and the top-down approach, namely artificial intelligence, reasoning and knowledge based methods. The three-fold goal of autonomous exploration, mapping and localization of a mobile robot however, needs to be developed within a single framework. An algorithm is proposed to answer the challenges of autonomous corridor navigation and mapping by a mobile robot equipped with a single forward-facing camera. Using a combination of corridor ceiling lights, visual homing, and entropy, the robot is able to perform straight line navigation down the center of an unknown corridor. Turning at the end of a corridor is accomplished using Jeffrey divergence and time-to-collision, while deflection from dead ends and blank walls uses a scalar entropy measure of the entire image. When combined, these metrics allow the robot to navigate in both textured and untextured environments. The robot can autonomously explore an unknown indoor environment, recovering from difficult situations like corners, blank walls, and initial heading toward a wall. While exploring, the algorithm constructs a Voronoi-based topo-geometric map with nodes representing distinctive places like doors, water fountains, and other corridors. Because the algorithm is based entirely upon low-resolution (32 x 24) grayscale images, processing occurs at over 1000 frames per second