Control of free-flying space robot manipulator systems

New control techniques for self contained, autonomous free flying space robots were developed and tested experimentally. Free flying robots are envisioned as a key element of any successful long term presence in space. These robots must be capable of performing the assembly, maintenance, and inspection, and repair tasks that currently require human extravehicular activity (EVA). A set of research projects were developed and carried out using lab models of satellite robots and a flexible manipulator. The second generation space robot models use air cushion vehicle (ACV) technology to simulate in 2-D the drag free, zero g conditions of space. The current work is divided into 5 major projects: Global Navigation and Control of a Free Floating Robot, Cooperative Manipulation from a Free Flying Robot, Multiple Robot Cooperation, Thrusterless Robotic Locomotion, and Dynamic Payload Manipulation. These projects are examined in detail

Analysing the behaviour of robot teams through relational sequential pattern mining

This report outlines the use of a relational representation in a Multi-Agent domain to model the behaviour of the whole system. A desired property in this systems is the ability of the team members to work together to achieve a common goal in a cooperative manner. The aim is to define a systematic method to verify the effective collaboration among the members of a team and comparing the different multi-agent behaviours. Using external observations of a Multi-Agent System to analyse, model, recognize agent behaviour could be very useful to direct team actions. In particular, this report focuses on the challenge of autonomous unsupervised sequential learning of the team's behaviour from observations. Our approach allows to learn a symbolic sequence (a relational representation) to translate raw multi-agent, multi-variate observations of a dynamic, complex environment, into a set of sequential behaviours that are characteristic of the team in question, represented by a set of sequences expressed in first-order logic atoms. We propose to use a relational learning algorithm to mine meaningful frequent patterns among the relational sequences to characterise team behaviours. We compared the performance of two teams in the RoboCup four-legged league environment, that have a very different approach to the game. One uses a Case Based Reasoning approach, the other uses a pure reactive behaviour.Comment: 25 page

Automated Verification and Generation of Flexible Automation Control

Consumer product life-cycles are constantly shortening; the automotive industry is an illustrative example. As a consequence, the introduction of new products into the manufacturing system necessarily becomes more frequent. Inherently, this brings a performance reduction for the manufacturing system. The reduced performance is caused by a down-time and a ramp-up-time. During the down-time the mechanical equipment is rebuilt and the new control programs are debugged. During ramp-up there are a large number of errors mainly caused by mechanical devices not being properly adjusted, bugs in the control programs and operators not used to new procedures. Thus, in order to maintain the productivity level and to achieve full cost-efficiency both the down-time and the ramp-up time must be reduced. One way to reduce these lead times is to verify the control programs in offline mode. However, efficient and reliable offline verification requires some major improvements of the current development process of manufacturing systems. Information handling and development of control programs based on information reuse are the two most important improvement areas.The work presented here addresses four industrial problems related to this, lack of tools for offline verification of control programs, lack of information reuse in the development process of a manufacturing system, lack of operator support in error situations, and lack of tools for analyzing the control of complex manufacturing cells.We propose a development method where information from different tools in the development process of a manufacturing system is reused and processed by tools for verification and optimization. Then the control programs are generated by combining the processed information with a library of standardized software components. The proposed method solves the above-mentioned industrial problems without adding work to the development process. On the contrary, the amount of work will be reduced since the control program development will be automated and the time for debugging the control programs on the shop floor will be drastically reduced, due to the new mathematically based verification process

Multirobot heterogeneous control considering secondary objectives

Cooperative robotics has considered tasks that are executed frequently, maintaining the shape and orientation of robotic systems when they fulfill a common objective, without taking advantage of the redundancy that the robotic group could present. This paper presents a proposal for controlling a group of terrestrial robots with heterogeneous characteristics, considering primary and secondary tasks thus that the group complies with the following of a path while modifying its shape and orientation at any time. The development of the proposal is achieved through the use of controllers based on linear algebra, propounding a low computational cost and high scalability algorithm. Likewise, the stability of the controller is analyzed to know the required features that have to be met by the control constants, that is, the correct values. Finally, experimental results are shown with di erent configurations and heterogeneous robots, where the graphics corroborate the expected operation of the proposalThis research was funded by Corporación Ecuatoriana para el Desarrollo de la Investigación y Academia–CEDI

Research and development of robots cooperation and coordination algorithm for space exploration

Las técnicas y métodos descritos en esta tesis están enfocados en resolver el problema de localización entre robots y del movimiento en una formación predeterminada. Para hacer esto será desarrollado un módulo coordinador y un módulo de seguimiento de objetivos como parte de la TBRA (Test Bench for Robotics and Autonomy) desarrollado previamente por Thales Alenia Space Italia y la Universidad de Genova. Todas las técnicas y métodos van a ser implementados en el lenguaje C++. Los módulos desarrollados serán probados usando los dos robots descritos en la tesis, el TBRA Robotic Platform y el Pioneer 3-AT.The technics and methods developed in this thesis are going to be focused on solving the problems of relative localization amongst robots and their movement maintaining a predetermined formation. To do this, it is going to be developed a coordinator module and a target tracking module, as a part of the TBRA (Test Bench for Robotics and Autonomy) previously developed in Thales Alenia Space Italia and the University of Genoa. All the technics and methods are going to be implemented in C++ language. The developed modules are going to be tested using the two robots described in the thesis, the TBRA Robotic Platform and the Pioneer 3-AT.Ingeniero (a) ElectrónicoPregrad

Self-adaptive decision-making mechanisms to balance the execution of multiple tasks for a multi-robots team

This work addresses the coordination problem of multiple robots with the goal of finding specific hazardous targets in an unknown area and dealing with them cooperatively. The desired behaviour for the robotic system entails multiple requirements, which may also be conflicting. The paper presents the problem as a constrained bi-objective optimization problem in which mobile robots must perform two specific tasks of exploration and at same time cooperation and coordination for disarming the hazardous targets. These objectives are opposed goals, in which one may be favored, but only at the expense of the other. Therefore, a good trade-off must be found. For this purpose, a nature-inspired approach and an analytical mathematical model to solve this problem considering a single equivalent weighted objective function are presented. The results of proposed coordination model, simulated in a two dimensional terrain, are showed in order to assess the behaviour of the proposed solution to tackle this problem. We have analyzed the performance of the approach and the influence of the weights of the objective function under different conditions: static and dynamic. In this latter situation, the robots may fail under the stringent limited budget of energy or for hazardous events. The paper concludes with a critical discussion of the experimental results