Autonomous Task-Based Evolutionary Design of Modular Robots

In an attempt to solve the problem of finding a set of multiple unique modular robotic designs that can be constructed using a given repertoire of modules to perform a specific task, a novel synthesis framework is introduced based on design optimization concepts and evolutionary algorithms to search for the optimal design. Designing modular robotic systems faces two main challenges: the lack of basic rules of thumb and design bias introduced by human designers. The space of possible designs cannot be easily grasped by human designers especially for new tasks or tasks that are not fully understood by designers. Therefore, evolutionary computation is employed to design modular robots autonomously. Evolutionary algorithms can efficiently handle problems with discrete search spaces and solutions of variable sizes as these algorithms offer feasible robustness to local minima in the search space; and they can be parallelized easily to reducing system runtime. Moreover, they do not have to make assumptions about the solution form. This dissertation proposes a novel autonomous system for task-based modular robotic design based on evolutionary algorithms to search for the optimal design. The introduced system offers a flexible synthesis algorithm that can accommodate to different task-based design needs and can be applied to different modular shapes to produce homogenous modular robots. The proposed system uses a new representation for modular robotic assembly configuration based on graph theory and Assembly Incidence Matrix (AIM), in order to enable efficient and extendible task-based design of modular robots that can take input modules of different geometries and Degrees Of Freedom (DOFs). Robotic simulation is a powerful tool for saving time and money when designing robots as it provides an accurate method of assessing robotic adequacy to accomplish a specific task. Furthermore, it is difficult to predict robotic performance without simulation. Thus, simulation is used in this research to evaluate the robotic designs by measuring the fitness of the evolved robots, while incorporating the environmental features and robotic hardware constraints. Results are illustrated for a number of benchmark problems. The results presented a significant advance in robotic design automation state of the art

A Modular Robotic System with Applications to Space Exploration

Modular robotic systems offer potential advantages as versatile, fault-tolerant, cost-effective platforms for space exploration, but a sufficiently mature system is not yet available. We describe the possible applications of such a system, and present prototype hardware intended as a step in the right direction. We also present elements of an automated design and optimization framework aimed at making modular robots easier to design and use, and discuss the results of applying the system to a gait optimization problem. Finally, we discuss the potential near-term applications of modular robotics to terrestrial robotics research

A semi-autonomous mobile robot for education and research

AbstractThis paper presents the development, implementation, and testing of a semi-autonomous robotic platform, which may potentially be used for educational and research purposes. Educational purposes include: teaching the student how to design a stable electromechanical platform, exploring different types of sensors to navigate around any obstacles, interfacing different electronic components to a microcontroller, and demonstrating how to program the microcontroller chip in order to control a robotic platform. Research purposes include: developing and investigating the performance of different control algorithms to achieve behaviour analysis and obstacles avoidance. A modular hardware design is implemented using I2C bus to interface different sensors and motor drivers to the ATMEL microcontroller chip (AVR ATmega32). The hardware is integrated in one application board as embedded system design. The software is developed using C-compiler (ImageCraft) and a top-down approach is adopted to design different software modules. Experimental results are given to demonstrate the potential of the developed hardware and software modules

Modular Self-Reconfigurable Robot Systems

The field of modular self-reconfigurable robotic systems addresses the design, fabrication, motion planning, and control of autonomous kinematic machines with variable morphology. Modular self-reconfigurable systems have the promise of making significant technological advances to the field of robotics in general. Their promise of high versatility, high value, and high robustness may lead to a radical change in automation. Currently, a number of researchers have been addressing many of the challenges. While some progress has been made, it is clear that many challenges still exist. By illustrating several of the outstanding issues as grand challenges that have been collaboratively written by a large number of researchers in this field, this article has shown several of the key directions for the future of this growing fiel

FPGA Processor Implementation for the Forward Kinematics of the UMDH

The focus of this research was on the implementation of a forward kinematic algorithm for the Utah MIT Dexterous Hand (UMDH). Specifically, the algorithm was synthesized from mathematical models onto a Field Programmable Gate Array (FPGA) processor. This approach is different from the classical, general purpose microprocessor design where all robotic controller functions including forward Kinematics are executed serially from a compiled programming language such as C. The compiled code and subsequent real time operating system must be stored on some form of nonvolatile memory, typically magnetic media such as a fixed or hard disk drive, along with other computer hardware components to allow the user to load and execute the software. With a future goal of moving the controllers to a portable platform like a dexterous prosthetic hand for amputee patients, the application of such a hardware implementation is impossible. Instead, this research explores a different implementation based on a modular approach of dedicated hardware controllers. The controller for the forward kinematics of the UMDH is used as a test case. The resulting FPGA processor replaces a robotic system\u27s burden of repetitive and discrete software system calls with a stand alone hardware interface that appears more like a single hardware function call. The robotic system is free to tackle other tasks while the FPGA processor is busy computing the results of the algorithm