TORP: An open standard framework for humanoid robots

Humanoid robots are an extremely complex interdisciplinary research field. Particularly, the development of high size humanoid robots usually requires joint efforts and skills from groups that are in many different research centers around the world. However, there are serious constraints in this kind of collaborative development. Some efforts have been made in order to propose new software frameworks that can allow distributed development with also some degree of hardware abstraction, allowing software reuse in successive projects. However, computation represents only one of the dimensions in robotics tasks, and the need for reuse and exchange of full robot modules between groups are growing. Large advances could be reached if physical parts of a robot could be reused in a different robot constructed with other technologies by other researcher or group. This paper proposes a new robot framework, from now on called TORP (The Open Robot Project), that aims to provide a standard architecture in all dimensions (electrical, mechanical and computational) for this collaborative development. This methodology also represents an open project that is fully shared. In this paper, the first robot constructed following the TORP specification set is presented as well as the advances proposed for its improvement. © 2010 IEEE.

A framework for learning in humanoid simulated robots

One of the most important characteristics of intelligent activity is the ability to change behaviour according to many forms of feedback. Through learning an agent can interact with its environment to improve its performance over time. However, most of the techniques known that involves learning are time expensive, i.e., once the agent is supposed to learn over time by experimentation, the task has to be executed many times. Hence, high fidelity simulators can save a lot of time. In this context, this paper describes the framework designed to allow a team of real RoboNova-I humanoids robots to be simulated under USARSim environment. Details about the complete process of modeling and programming the robot are given, as well as the learning methodology proposed to improve robot's performance. Due to the use of a high fidelity model, the learning algorithms can be widely explored in simulation before adapted to real robots. © 2008 Springer-Verlag Berlin Heidelberg.

TORP: The Open Robot Project A Framework for Module-Based Robots

The development of robots has shown itself as a very complex interdisciplinary research field. The predominant procedure for these developments in the last decades is based on the assumption that each robot is a fully personalized project, with the direct embedding of hardware and software technologies in robot parts with no level of abstraction. Although this methodology has brought countless benefits to the robotics research, on the other hand, it has imposed major drawbacks: (i) the difficulty to reuse hardware and software parts in new robots or new versions; (ii) the difficulty to compare performance of different robots parts; and (iii) the difficulty to adapt development needs-in hardware and software levels-to local groups expertise. Large advances might be reached, for example, if physical parts of a robot could be reused in a different robot constructed with other technologies by other researcher or group. This paper proposes a framework for robots, TORP (The Open Robot Project), that aims to put forward a standardization in all dimensions (electrical, mechanical and computational) of a robot shared development model. This architecture is based on the dissociation between the robot and its parts, and between the robot parts and their technologies. In this paper, the first specification for a TORP family and the first humanoid robot constructed following the TORP specification set are presented, as well as the advances proposed for their improvement.

Robots, intencionalidade e inteligência artificial

O artigo aborda problemas filosóficos relativos à natureza da intencionalidade e da representação mental. A primeira parte apresenta um breve histórico dos problemas, percorrendo rapidamente alguns episódios da filosofia clássica e da filosofia contemporânea. A segunda parte examina o Chinese Room Argument (Argumento do Quarto do Chinês) formulado por J. Searle. A terceira parte desenvolve alguns argumentos visando mostrar a inadequação do modelo funcionalista de mente na construção de robots. A conclusão (quarta parte) aponta algumas alternativas ao modelo funcionalista tradicional, como, por exemplo, o conexionismo.

Autonomous mobile robots designing for the medical trash collector task

This paper describes the UNESP robotic team in the medical trash collector task, proposed on the 5 rd IEEE Latin American Robots Competition in the LEGO category. We present our understanding of the task and discuss the proposed solution, focusing on the mechanical and computational issues of the robots. The mechanics is based on rigid body capability of transforming rotational into curvilinear movement. With respect to the computational control, the system is modeled as a reactive system with sequential transition of behaviors. A state-machine is proposed to allow this transition, and the synchronization of robotic states is guaranteed by the communication system. The proposed approach has shown itself capable of dealing with the high difficulty degree of this cooperative task. ©2006 IEEE.

Conception of wheeled mobile robots with reconfigurable control using integrate prototyping

With the fast innovation of the hardware and software technologies using rapid prototyping devices, with application in the robotics and automation, more and more it becomes necessary the development of applications based on methodologies that facilitate future modifications, updates and enhancements in the original projected system. This paper presents a conception of mobile robots using rapid prototyping, distributing the several control actions in growing levels of complexity and using resources of reconfigurable computing proposal oriented to embed systems implementation. Software and the hardware are structuralized in independents blocks, with connection through common bus. The study and applications of new structures control that permits good performance in relation to the parameter variations. This kind of controller can be tested on different platform representing the wheeled mobile robots using reprogrammable logic components (FPGA). © 2006 IEEE.

Virtual simulator for mobile robots navigation systems

This paper presents the virtual environment implementation for project simulation and conception of supervision and control systems for mobile robots, that are capable to operate and adapting in different environments and conditions. This virtual system has as purpose to facilitate the development of embedded architecture systems, emphasizing the implementation of tools that allow the simulation of the kinematic conditions, dynamic and control, with real time monitoring of all important system points. For this, an open control architecture is proposal, integrating the two main techniques of robotic control implementation in the hardware level: systems microprocessors and reconfigurable hardware devices. The implemented simulator system is composed of a trajectory generating module, a kinematic and dynamic simulator module and of a analysis module of results and errors. All the kinematic and dynamic results shown during the simulation can be evaluated and visualized in graphs and tables formats, in the results analysis module, allowing an improvement in the system, minimizing the errors with the necessary adjustments optimization. For controller implementation in the embedded system, it uses the rapid prototyping, that is the technology that allows, in set with the virtual simulation environment, the development of a controller project for mobile robots. The validation and tests had been accomplish with nonholonomics mobile robots models with diferencial transmission. © 2008 IEEE.

Environment mapping for mobile robots navigation using hierarchical neural network and omnivision

Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

TAO - A software platform for autonomous mobile robots

To date, different techniques of navigation for mobile robots have been developed. However, the experimentation of these techniques is not a trivial task because usually it is not possible to reuse the developed control software due to system incompabilities. This paper proposes a software platform that provides means for creating reusable software modules through the standardization of software interfaces, which represent the various robot modules. © 2012 ICROS.

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science