TRIDENT: A Framework for Autonomous Underwater Intervention

TRIDENT is a STREP project recently approved by the European Commission whose proposal was submitted to the ICT call 4 of the 7th Framework Program. The project proposes a new methodology for multipurpose underwater intervention tasks. To that end, a cooperative team formed with an Autonomous Surface Craft and an Intervention Autonomous Underwater Vehicle will be used. The proposed methodology splits the mission in two stages mainly devoted to survey and intervention tasks, respectively. The project brings together research skills specific to the marine environments in navigation and mapping for underwater robotics, multi-sensory perception, intelligent control architectures, vehiclemanipulator systems and dexterous manipulation. TRIDENT is a three years project and its start is planned by first months of 2010.This work is partially supported by the European Commission through FP7-ICT2009-248497 projec

ROAZ Autonomous Surface Vehicle Design and Implementation

The design of an Autonomous Surface Vehicle for operation in river and estuarine scenarios is presented. Multiple operations with autonomous underwater vehicles and support to AUV missions are one of the main design goals in the ROAZ system. The mechanical design issues are discussed. Hardware, software and implementation status are described along with the control and navigation system architecture. Some preliminary test results concerning a custom developed thruster are presented along with hydrodynamic drag calculations by the use of computer fluid dynamic methods

PEIS stol: autonomni robotski stol za kućanstva

There are two main trends in the area of home and service robotics. The classical one aims at the development of a single skilled servant robot, able to perform complex tasks in a passive environment. The second, more recent trend aims at the achievement of complex tasks through the cooperation of a network of simpler robotic devices pervasively embedded in the domestic environment. This paper contributes to the latter trend by describing the PEIS Table, an autonomous robotic table that can be embedded in a smart environment. The robotic table can operate alone, performing simple point-to-point navigation, or it can collaborate with other devices in the environment to perform more complex tasks. Collaboration follows the PEIS Ecology model. The hardware and software design of the PEIS Table are guided by a set of requirements for robotic domestic furniture that differ, to some extent, from the requirements usually considered for service robots.U uslužnoj robotici i robotici za kućanstva postoje dva glavna trenda. Klasičan pristup teži razvoju jednog složenog uslužnog robota koji je sposoban izvršavati složene zadatke u pasivnom okruženju. Dok drugi, nešto noviji pristup, teži rješavanju složenih zadataka kroz suradnju umreženih nešto jednostavnijih robota prožetih kroz cijelo kućanstvo. Ovaj članak svoj doprinos daje drugom pristupu opisujući PEIS stol, autonomni robotski stol koji se može postaviti u inteligentnom okruženju. Robotski stol može djelovati samostalno, navigirajući od točke do točke ili može surađivati s ostalim uređajima u okruženju radi izvršavanja složenijih zadataka. Ta suradnja prati PEIS ekološki model. Dizajn sklopovlja i programske podrške PEIS stola prati zahtjeve za robotsko pokućstvo koji se donekle razlikuju od zahtjeva koji se inače postavljaju za uslužne robote

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Advancing automation and robotics technology for the space station and for the US economy: Submitted to the United States Congress October 1, 1987

In April 1985, as required by Public Law 98-371, the NASA Advanced Technology Advisory Committee (ATAC) reported to Congress the results of its studies on advanced automation and robotics technology for use on the space station. This material was documented in the initial report (NASA Technical Memorandum 87566). A further requirement of the Law was that ATAC follow NASA's progress in this area and report to Congress semiannually. This report is the fifth in a series of progress updates and covers the period between 16 May 1987 and 30 September 1987. NASA has accepted the basic recommendations of ATAC for its space station efforts. ATAC and NASA agree that the mandate of Congress is that an advanced automation and robotics technology be built to support an evolutionary space station program and serve as a highly visible stimulator affecting the long-term U.S. economy

Recent Progress in the RAUVI Project: A Reconfigurable Autonomous Underwater Vehicle for Intervention

Starting in January 2009, the RAUVI project is a three years coordinated research action funded by the Spanish Ministry of Research and Innovation. This paper shows the research evolution during the first half of RAUVI’s live, bearing in mind that the long term objective is to design and develop an underwater autonomous robot able to perceive the environment and, by means of a specific hand-arm system, perform autonomously simple intervention tasks in shallow waters.This research was partly supported by the European Commission’s Seventh Framework Programme FP7/2007- 2013 under grant agreement 248497 (TRIDENT Project), by Spanish Ministry of Research and Innovation DPI2008-06548- C03 (RAUVI Project), and by Fundació Caixa Castelló- Bancaixa P1-1B2009-50

Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue

Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion

Looking Back and Looking Forward: Reprising the Promise and Predicting the Future of Formation Flying and Spaceborne GPS Navigation Systems

A retrospective consideration of two 15-year old Guidance, Navigation and Control (GN&C) technology 'vision' predictions will be the focus of this paper. A look back analysis and critique of these late 1990s technology roadmaps out-lining the future vision, for two then nascent, but rapidly emerging, GN&C technologies will be performed. Specifically, these two GN&C technologies were: 1) multi-spacecraft formation flying and 2) the spaceborne use and exploitation of global positioning system (GPS) signals to enable formation flying. This paper reprises the promise of formation flying and spaceborne GPS as depicted in the cited 1999 and 1998 papers. It will discuss what happened to cause that promise to be mostly unfulfilled and the reasons why the envisioned formation flying dream has yet to become a reality. The recent technology trends over the past few years will then be identified and a renewed government interest in spacecraft formation flying/cluster flight will be highlighted. The authors will conclude with a reality-tempered perspective, 15 years after the initial technology roadmaps were published, predicting a promising future of spacecraft formation flying technology development over the next decade

Configuration Recognition, Communication Fault Tolerance and Self-reassembly for the CKBot

We present and experimentally verify novel methods for increasing the generality of control, autonomy and reliability for modular robotic systems. In particular, we demonstrate configuration recognition, distributed communication fault tolerance, and the organization and control of self-reassembly with the Connector Kinetic roBot (CKBot). The primary contribution of this work is the presentation and experimental verification of these innovative methods that are general and applicable to other modular robotic systems. We describe our CKBot system and compare it to other similar, state-of-the-art modular robotic systems. Our description and comparison highlights various design developments, features, and notable achievements of these systems. We present work on isomorphic configuration recognition with CKBot. Here, we utilize basic principles from graph theory to create and implement an algorithm on CKBot that automatically recognizes modular robot configurations. In particular, we describe how comparing graph spectra of configuration matrices can be used to find a permutation matrix that maps a given configuration to a known one. If a configuration is matched to one in a library of stored gaits, a permutation mapping is applied and the corresponding coordinated control for locomotion is executed. An implementation of the matching algorithm with small configurations of CKBot configurations that can be rearranged during runtime is presented. We also present work on a distributed fault-tolerance algorithm used to control CKBot configurations. Here, we use a triple modular redundancy approach for CKBot units to collectively vote on observations and execute commands in the presence of infrared (IR) communication failures. In our implementation, we broadcast infrared signals to modules which collaboratively vote on a majority course of action. Various gait selections for a seven module caterpillar and sixteen module quadruped with faulty subsets of IR receivers have been verified to demonstrate the algorithm\u27s robustness. Lastly, we present work on the communication hierarchy and control state machine for the Self-reassembly After Explosion (SAE) robot. Here, we discuss the interaction and integration of the various sensory inputs and control outputs implemented for camera-guided self-reassembly with CKBot. This section describes the overall communication system and reassembly sequence planning after a group of CKBot clusters is kicked apart