46 research outputs found
Emergent velocity agreement in robot networks
In this paper we propose and prove correct a new self-stabilizing velocity
agreement (flocking) algorithm for oblivious and asynchronous robot networks.
Our algorithm allows a flock of uniform robots to follow a flock head emergent
during the computation whatever its direction in plane. Robots are
asynchronous, oblivious and do not share a common coordinate system. Our
solution includes three modules architectured as follows: creation of a common
coordinate system that also allows the emergence of a flock-head, setting up
the flock pattern and moving the flock. The novelty of our approach steams in
identifying the necessary conditions on the flock pattern placement and the
velocity of the flock-head (rotation, translation or speed) that allow the
flock to both follow the exact same head and to preserve the flock pattern.
Additionally, our system is self-healing and self-stabilizing. In the event of
the head leave (the leading robot disappears or is damaged and cannot be
recognized by the other robots) the flock agrees on another head and follows
the trajectory of the new head. Also, robots are oblivious (they do not recall
the result of their previous computations) and we make no assumption on their
initial position. The step complexity of our solution is O(n)
On Asynchrony, Memory, and Communication: Separations and Landscapes
Research on distributed computing by a team of identical mobile computational
entities, called robots, operating in a Euclidean space in
-- () cycles, has
recently focused on better understanding how the computational power of robots
depends on the interplay between their internal capabilities (i.e., persistent
memory, communication), captured by the four standard computational models
(OBLOT, LUMI, FSTA, and FCOM) and the conditions imposed by the external
environment, controlling the activation of the robots and their synchronization
of their activities, perceived and modeled as an adversarial scheduler.
We consider a set of adversarial asynchronous schedulers ranging from the
classical semi-synchronous (SSYNCH) and fully asynchronous (ASYNCH) settings,
including schedulers (emerging when studying the atomicity of the combination
of operations in the cycles) whose adversarial power is in
between those two. We ask the question: what is the computational relationship
between a model under adversarial scheduler () and a
model under scheduler ()? For example, are the robots in
more powerful (i.e., they can solve more problems) than those in
?
We answer all these questions by providing, through cross-model analysis, a
complete characterization of the computational relationship between the power
of the four models of robots under the considered asynchronous schedulers. In
this process, we also provide qualified answers to several open questions,
including the outstanding one on the proper dominance of SSYNCH over ASYNCH in
the case of unrestricted visibility
Verification of Autonomous Systems: Developmental Test and Evaluation of an Autonomous UAS Swarming Algorithm Combining Simulation, Formulation and Live Flight
This research was driven by the increase of autonomous systems in the current millennium and the challenging nature of testing and evaluating their performance. A review of the current literature revealed proposed methods for verifying autonomous systems, but few implementations. It exposed several gaps in the current verification and validation methods and suggested goals for filling them. Through the use of modeling, software in the loop (SITL), and flight test, this research verified an autonomous swarming algorithm for unmanned aerial systems (UAS) and validated an exemplar of a testing framework. Thirteen sets of three-vehicle swarm data produced over two days of flight testing provided a baseline algorithm analysis. During these tests, vehicle separation distances deviated an average of 5.61 meters from the ideal state, with separation distance violations \u3c 6:39% of the time. The swarm achieved a 0.27 m average deviation and 0.43% violation in the best cases. Average packet loss between vehicles was 4.94% at a 5 Hz update rate, with an optimal communication lag \u3c 0:04 seconds. The multi-faceted empirical analysis created through the pairing of qualitative and quantitative analysis provided a complete understanding of vehicle behavior. This analysis also identified various areas of improvement for the algorithm and testing framework. The outcomes of this research formed a baseline testing continuum that is adaptable to a variety of follow-on investigations into formal verification of autonomous systems
Virtual stationary timed automata for mobile networks
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (p. 339-347).In this thesis, we formally define a programming abstraction for mobile networks called the Virtual Stationary Automata programming layer, consisting of real mobile clients, virtual timed I/O automata called virtual stationary automata (VSAs), and a communication service connecting VSAs and client nodes. The VSAs are located at prespecified regions that tile the plane, defining a static virtual infrastructure. We present a theory of self-stabilizing emulation and use this theory to prove correct a self-stabilizing algorithm to emulate a timed VSA using the real mobile nodes that are currently residing in the VSA's region. We also specify two important services for mobile networks: motion coordination and end-to-end routing. We split the implementation of the end-to-end routing service into three smaller pieces, consisting of geographic routing and location management services with an end-to-end routing service built on top of them. We provide stabilizing implementations of each of these services using the VSA abstraction, and provide formal correctness analyses for each implementation.by Tina Ann Nolte.Ph.D
Methods for the Efficient Deployment and Coordination of Swarm Robotic Systems
Swarming has been observed in many animal species, including fish, birds, insects and mammals. These biological observations have inspired mathematical models of distributed coordination that have been applied to the development of multi-agent robotic systems, such as collections of unmanned autonomous vehicles (UAVs). The advantages of a swarming approach to distributed coordination are clear: each agent acts according to a simple set of rules that can be implemented on resource-constrained devices, and so it becomes feasible to replicate agents in order to build more resilient systems. However, there remain significant challenges in making the approach practicable. This thesis addresses two of the most significant: coordination and scalability. New coordination algorithms are proposed here, all of which manage the problem of scalability by requiring only local proximity sensing between agents, without the need for any other communications infrastructure.
A major source of inefficiency in the deployment of a swarm is ‘oscillation’: small movements of agents that arise as a side effect of the application of their rules but which are not strictly necessary in order to satisfy the overall system function. The thesis introduces a new metric for ‘oscillation’ that allows it to be identified and measured in swarm control algorithms.
A new perimeter detection mechanism is introduced and applied to the coordination of goal-based swarms. The mechanism is used to improve the internal coordination of agents whilst maintaining a directional focus to the swarm; this is then analysed using the new metric.
A mechanism is proposed to allow a swarm to exhibit a ‘healing’ behaviour by identifying internal perimeter edges (doughnuts) and then altering the movement of agents, based upon a simple criterion, to remove the holes; this also has the emergent effect of smoothing the outer edges of a swarm and creating a more uniform swarm structure.
Area coverage is an important requirement in many swarm applications. Two new, efficient area-filling techniques are introduced here and exit conditions are identified to determine when a swarm has filled an area. In summary, the thesis makes significant contributions to the analysis and design of efficient control algorithms for the coordination of large scale swarms