Search

Self-assembly is a key coordination mechanism for distributed systems of intelligent agents and a powerful bottom-up technology for micro/nanofabrication. The controlled self-assembly and dynamic reconfiguration of large ensembles of microscopic particles can effectively bridge these domains to construct innovative systems. In this perspective, we present SelfSys, a novel platform for the automated control of the fluidic self-assembly of sets of polymeric microparticles. SelfSys is built around a water-filled microfluidic chamber whereby self-assembly is driven by the agitation modes induced by a coupled ultrasonic actuator. Microparticle dynamics is imaged, tracked and analyzed in real-time by an integrated software framework which in turn algorithmically controls the actuation modes of the microchamber. The closed control loop is fully automated and can direct the stochastic assembly of microparticle clusters of preset dimension. Control issues specific to SelfSys implementation are discussed, and its potential applications presented. The SelfSys platform embodies at microscale the automatedself-assembly control paradigm we first demonstrated in an earlier platform, info:eu-repo/semantics/published

info:eu-repo/semantics/published

We present an innovative design and fabrication process for three-dimensional polymeric microtiles. Our 200 µm-sized tiles are passive vehicles designed to investigate SA in a microfluidic chamber, as an extension of our centimeter scale studies [5]. They are conceived by superposing two structural layers with inverted chiral patterns and fourfold in-plane symmetry (Fig. 1a). The tiles interact laterally, either at a liquid/liquid interface or in bulk liquid (Fig. 2). The design makes the tiles available for coordination independently of their vertical orientation, unlike e.g. [4]. They also feature a central marker for optical tracking and control (Fig. 1b). The microtiles—with overhanging and straight walls needed for intimatecontact—cannot evidently be fabricated by microstereolithography or by simple lithographical patterning., info:eu-repo/semantics/published

In this paper, we present the theoretical background, design, fabrication and characterization of a micromachined chamber assisting the fluidic self-assembly of micro-electro-mechanical systems in a bulk liquid. Exploiting bubble-induced acoustic microstreaming, several structurally-robust driving modes are excited inside the chamber. The modes promote the controlled aggregation and disaggregation of microcomponents relying on strong and reproducible fluid mixing effects achieved even at low Reynolds numbers. The functionality of the microfluidic chamber is demonstrated through the fast and repeatable geometrical pairing and subsequent unpairing of polymeric microcylinders. Relying only on drag and radiation forces and on the natural hydrophobicity of SU-8 in aqueous solutions, assembly yields of approximately 50% are achieved in no longer than ten seconds of agitation. The system can stochastically control the assembly process and significantly reduce the time-to-assembly of building blocks., info:eu-repo/semantics/published

Autonomous Underwater Vehicles (AUVs) are used for an ever increasing range of applications due to the maturing of the technology. Due to the absence of the GPS signal underwater, the correct estimation of its position is a challenge for submerged vehicles. One promising strategy to mitigate this problem is to use a group of AUVs where one or more assume the role of a beacon vehicle which has a very accurate position estimate due to an expensive navigation suite or frequent surfacings. These beacon vehicles broadcast their position and the remaining survey vehicles can use this position information and intra-vehicle ranges to update their position estimate. The effectiveness of this approach strongly depends on the geometry between the beacon vehicles and the survey vehicles. The trajectories of the beacon vehicles should thus be planned with the goal to minimize the position uncertainty of the survey vehicles. We propose a distributed algorithm which dynamically computes the locally optimal position for a beacon vehicle using only information obtained from broadcast communication of the survey vehicles. It does not need prior information about the survey vehicles' trajectory and can be used for any group size of beacon and survey vehicles., United States. Office of Naval Research (Grant N00014-97-1-0202), United States. Office of Naval Research (Grant N00014-05-1-0255), United States. Office of Naval Research (Grant N00014-02-C- 0210), United States. Office of Naval Research (Grant N00014-07-1-1102)

We present the M 3 framework, a formal and generic computational framework for modeling and controlling stochastic distributed systems of purely reactive robots in an automated and real-time fashion. Based on the trajectories of the robots, the framework builds up an internal microscopic representation of the system, which then serves as a blueprint of models at higher abstraction levels. These models are then calibrated using a Maximum Likelihood Estimation (MLE) algorithm. We illustrate the structure and performance of the framework by performing the online optimization of a bang-bang controller for the stochastic self-assembly of water-floating, magnetically latching, passive modules. The experimental results demonstrate that the generated models can successfully optimize the assembly of desired structures., info:eu-repo/semantics/published

A wealth of current research in microengineering aims at fabricating devices of increasing complexity, notably by (self-)assembling elementary components into heterogeneous functional systems. At the same time, a large body of robotic research called swarm robotics is concerned with the design and the control of large ensembles of robots of decreasing size and complexity. This paper describes the asymptotic convergence of micro/nano electromechanical systems (M/NEMS) on one side, and swarm robotic systems on the other, toward a unifying class of systems, which we denote Smart Minimal Particles (SMPs). We define SMPs as mobile, purely reactive and physically embodied agents that compensate for their limited on-board capabilities using specifically engineered reactivity to external physical stimuli, including local energy and information scavenging. In trading off internal resources for simplicity and robustness, SMPs are still able to collectively perform non-trivial, spatio-temporally coordinated and highly scalable operations such as aggregation and self-assembly (SA). We outline the opposite converging tendencies, namely M/NEMS smarting and robotic minimalism, by reviewing each field’s literature with specific focus on self-assembling systems. Our main claim is that the SMPs can be used to develop a unifying technological and methodological framework that bridges the gap between passive M/NEMS and active, centimeter-sized robots. By proposing this unifying perspective, we hypothesize a continuum in both complexity and length scale between these two extremes. We illustrate the benefits of possible cross-fertilizations among these originally separate domains, with specific emphasis on the modeling of collective dynamics. Particularly, we argue that while most of the theoretical studies on M/NEMS SA dynamics belong so far to one of only two main frameworks—based on analytical master equations and on numerical agent-based simulations, respectively—alternative models develo, info:eu-repo/semantics/published

In this paper, we present a quantitative, trajectory-based method for calibrating stochastic motion models of water-floating robots. Our calibration method is based on the Correlated Random Walk (CRW) model, and consists in minimizing the Kolmogorov-Smirnov (KS) distancebetween the step length and step angle distributions of real and simulated trajectories generated by the robots. First, we validate this method by calibrating a physics-based motion model of a single 3-cm-sized robot floating at a water/air interface under fluidic agitation. Second, we extend the focus of our work to multi-robot systems by performing a sensitivity analysis of our stochastic motion model in the context of Self-Assembly (SA). In particular, we compare in simulation the effect of perturbing the calibrated parameters on the predicted distributions of self-assembled structures. More generally, we show that the SA of water-floating robots is very sensitive to even small variations of the underlying physical parameters, thus requiring real-time tracking of its dynamics., info:eu-repo/semantics/published

Inspection of aircraft and power generation machinery using a swarm of miniature robots is a promising application both from an intellectual and a commercial perspective. Our research is motivated by a case study concerned with the inspection of a jet turbine engine by a swarm of miniature robots. This article summarizes our efforts that include multirobot path planning, modeling of self-organized robotic systems, and the implementation of proof-of-concept experiments with real miniature robots. Although other research tackles challenges that arise from moving within three-dimensional (3-D) structured environments at the level of the individual robotic node, the emphasis of our work is on explicitly incorporating the potential limitations of the individual robotic platform in terms of sensor and actuator noise into the modeling and design process of collaborative inspection systems. We highlight difficulties and further challenges on the (lengthy) path toward truly autonomous parallel robotic inspection of complex engineered structures., Swiss National Science Foundation, Caltech Center forNeuromorphic Systems Engineering

We study distributed boundary coverage of known environments using a team of miniature robots. Distributed boundary coverage is an instance of the multi-robot task-allocation problem and has applications in inspection, cleaning, and painting among others. The proposed algorithm is robust to sensor and actuator noise, failure of individual robots, and communication loss. We use a market-based algorithm with known lower bounds on the performance to allocate the environmental objects of interest among the team of robots. The coverage time for systems subject to sensor and actuator noise is significantly shortended by on-line task re-allocation. The complexity and convergence properties of the algorithm are formally analyzed. The system performance is systematically analyzed at two different microscopic modeling levels, using agent-based, discrete-event and module-based, realistic simulators. Finally, results obtained in simulation are validated using a team of Alice miniature robots involved in a distributed inspection case study.