Towards a Formal Verification Methodology for Collective Robotic Systems

We introduce a UML-based notation for graphically modeling systems’ security aspects in a simple and intuitive way and a model-driven process that transforms graphical specifications of access control policies in XACML. These XACML policies are then translated in FACPL, a policy language with a formal semantics, and the resulting policies are evaluated by means of a Java-based software tool

Workshop on "Robotic assembly of 3D MEMS".

Proceedings of a workshop proposed in IEEE IROS'2007.The increase of MEMS' functionalities often requires the integration of various technologies used for mechanical, optical and electronic subsystems in order to achieve a unique system. These different technologies have usually process incompatibilities and the whole microsystem can not be obtained monolithically and then requires microassembly steps. Microassembly of MEMS based on micrometric components is one of the most promising approaches to achieve high-performance MEMS. Moreover, microassembly also permits to develop suitable MEMS packaging as well as 3D components although microfabrication technologies are usually able to create 2D and "2.5D" components. The study of microassembly methods is consequently a high stake for MEMS technologies growth. Two approaches are currently developped for microassembly: self-assembly and robotic microassembly. In the first one, the assembly is highly parallel but the efficiency and the flexibility still stay low. The robotic approach has the potential to reach precise and reliable assembly with high flexibility. The proposed workshop focuses on this second approach and will take a bearing of the corresponding microrobotic issues. Beyond the microfabrication technologies, performing MEMS microassembly requires, micromanipulation strategies, microworld dynamics and attachment technologies. The design and the fabrication of the microrobot end-effectors as well as the assembled micro-parts require the use of microfabrication technologies. Moreover new micromanipulation strategies are necessary to handle and position micro-parts with sufficiently high accuracy during assembly. The dynamic behaviour of micrometric objects has also to be studied and controlled. Finally, after positioning the micro-part, attachment technologies are necessary

Spatio-Temporal Patterns act as Computational Mechanisms governing Emergent behavior in Robotic Swarms

open access articleOur goal is to control a robotic swarm without removing its swarm-like nature. In other words, we aim to intrinsically control a robotic swarm emergent behavior. Past attempts at governing robotic swarms or their selfcoordinating emergent behavior, has proven ineffective, largely due to the swarm’s inherent randomness (making it difficult to predict) and utter simplicity (they lack a leader, any kind of centralized control, long-range communication, global knowledge, complex internal models and only operate on a couple of basic, reactive rules). The main problem is that emergent phenomena itself is not fully understood, despite being at the forefront of current research. Research into 1D and 2D Cellular Automata has uncovered a hidden computational layer which bridges the micromacro gap (i.e., how individual behaviors at the micro-level influence the global behaviors on the macro-level). We hypothesize that there also lie embedded computational mechanisms at the heart of a robotic swarm’s emergent behavior. To test this theory, we proceeded to simulate robotic swarms (represented as both particles and dynamic networks) and then designed local rules to induce various types of intelligent, emergent behaviors (as well as designing genetic algorithms to evolve robotic swarms with emergent behaviors). Finally, we analysed these robotic swarms and successfully confirmed our hypothesis; analyzing their developments and interactions over time revealed various forms of embedded spatiotemporal patterns which store, propagate and parallel process information across the swarm according to some internal, collision-based logic (solving the mystery of how simple robots are able to self-coordinate and allow global behaviors to emerge across the swarm)

Design and Calibration of a Lightweight Physics-Based Model for Fluid-Mediated Self-Assembly of Robotic Modules

In this paper, we consider a system consisting of multiple floating robotic modules performing self-assembly. Faithfully modeling such a system and its inter-module interactions typically involves capturing the hydrodynamic forces acting on the modules using computationally expensive fluid dynamic modeling tools. This poses restrictions on the usability of the resulting models. Here, we present a new approach towards modeling such systems. First, we show how the hardware and firmware of the robotic modules can be faithfully modeled in a high-fidelity robotic simulator. Second, we develop a physics plugin to recreate the hydrodynamic forces acting on the modules and propose a trajectory-based method for calibrating the plugin model parameters. Our calibration method employs a Particle Swarm Optimization (PSO) algorithm, and consists of minimizing the difference between Mean Squared Displacement (MSD) data extracted from real and simulated trajectories of multiple robotic modules

Swarm robotics:design and implementation

This project presents a swarming and herding behaviour using simple robots. The main goal is to demonstrate the applicability of artificial intelligence (AI) in simple robotics that can then be scaled to industrial and consumer markets to further the ability of automation. AI can be achieved in many different ways; this paper explores the possible platforms on which to build a simple AI robots from consumer grade microcontrollers. Emphasis on simplicity is the main focus of this paper. Cheap and 8 bit microcontrollers were used as the brain of each robot in a decentralized swarm environment were each robot is autonomous but still a part of the whole. These simple robots don’t communicate directly with each other. They will utilize simple IR sensors to sense each other and simple limit switches to sense other obstacles in their environment. Their main objective is to assemble at certain location after initial start from random locations, and after converging they would move as a single unit without collisions. Using readily available microcontrollers and simple circuit design, semiconsistent swarming behaviour was achieved. These robots don’t follow a set path but will react dynamically to different scenarios, guided by their simple AI algorithm

Soft-bodied adaptive multimodal locomotion strategies in fluid-filled confined spaces

Soft-bodied locomotion in fluid-filled confined spaces is critical for future wireless medical robots operating inside vessels, tubes, channels, and cavities of the human body, which are filled with stagnant or flowing biological fluids. However, the active soft-bodied locomotion is challenging to achieve when the robot size is comparable with the cross-sectional dimension of these confined spaces. Here, we propose various control and performance enhancement strategies to let the sheet-shaped soft millirobots achieve multimodal locomotion, including rolling, undulatory crawling, undulatory swimming, and helical surface crawling depending on different fluid-filled confined environments. With these locomotion modes, the sheet-shaped soft robot can navigate through straight or bent gaps with varying sizes, tortuous channels, and tubes with a flowing fluid inside. Such soft robot design along with its control and performance enhancement strategies are promising to be applied in future wireless soft medical robots inside various fluid-filled tight regions of the human body

What do Collaborations with the Arts Have to Say About Human-Robot Interaction?

This is a collection of papers presented at the workshop What Do Collaborations with the Arts Have to Say About HRI , held at the 2010 Human-Robot Interaction Conference, in Osaka, Japan