32,844 research outputs found
Planar Cooperative Extremum Seeking with Guaranteed Convergence Using A Three-Robot Formation
In this paper, a combined formation acquisition and cooperative extremum
seeking control scheme is proposed for a team of three robots moving on a
plane. The extremum seeking task is to find the maximizer of an unknown
two-dimensional function on the plane. The function represents the signal
strength field due to a source located at maximizer, and is assumed to be
locally concave around maximizer and monotonically decreasing in distance to
the source location. Taylor expansions of the field function at the location of
a particular lead robot and the maximizer are used together with a gradient
estimator based on signal strength measurements of the robots to design and
analyze the proposed control scheme. The proposed scheme is proven to
exponentially and simultaneously (i) acquire the specified geometric formation
and (ii) drive the lead robot to a specified neighborhood disk around
maximizer, whose radius depends on the specified desired formation size as well
as the norm bounds of the Hessian of the field function. The performance of the
proposed control scheme is evaluated using a set of simulation experiments.Comment: Presented at the 2018 IEEE Conference on Decision and Control (CDC),
Miami Beach, FL, US
Distributed Source Seeking without Global Position Information
International audienceWe present a distributed control law to steer a group of autonomous communicating sensors towards the source of a diffusion process. The graph describing the communication links between sensors has a time-invariant topology, and each sensor is able to measure (in addition to the quantity of interest) only the relative bearing angle with respect to its neighbour, but has no absolute position information and does not know any relative distance. Using multiple sensors is useful in wide environments (e.g., under the sea), or when the function describing the diffusion process is slowly changing in space, so that a single sensor may have to travel long distances before having a good gradient estimation. Our approach is based on a twofold control law, which is able to bring and keep the set of sensors on a circular equispaced formation, and to steer the circular formation towards the source via a gradient-ascent technique. The effectiveness of the proposed algorithm is both theoretically proven and supported by simulation results
Human Swarm Interaction: An Experimental Study of Two Types of Interaction with Foraging Swarms
In this paper we present the first study of human-swarm interaction comparing two fundamental types of interaction, coined intermittent and environmental. These types are exemplified by two control methods, selection and beacon control, made available to a human operator to control a foraging swarm of robots. Selection and beacon control differ with respect to their temporal and spatial influence on the swarm and enable an operator to generate different strategies from the basic behaviors of the swarm. Selection control requires an active selection of groups of robots while beacon control exerts an influence on nearby robots within a set range. Both control methods are implemented in a testbed in which operators solve an information foraging problem by utilizing a set of swarm behaviors. The robotic swarm has only local communication and sensing capabilities. The number of robots in the swarm range from 50 to 200. Operator performance for each control method is compared in a series of missions in different environments with no obstacles up to cluttered and structured obstacles. In addition, performance is compared to simple and advanced autonomous swarms. Thirty-two participants were recruited for participation in the study. Autonomous swarm algorithms were tested in repeated simulations. Our results showed that selection control scales better to larger swarms and generally outperforms beacon control. Operators utilized different swarm behaviors with different frequency across control methods, suggesting an adaptation to different strategies induced by choice of control method. Simple autonomous swarms outperformed human operators in open environments, but operators adapted better to complex environments with obstacles. Human controlled swarms fell short of task-specific benchmarks under all conditions. Our results reinforce the importance of understanding and choosing appropriate types of human-swarm interaction when designing swarm systems, in addition to choosing appropriate swarm behaviors
Resilient source seeking with robot swarms
We present a solution for locating the source, or maximum, of an unknown
scalar field using a swarm of mobile robots. Unlike relying on the traditional
gradient information, the swarm determines an ascending direction to approach
the source with arbitrary precision. The ascending direction is calculated from
measurements of the field strength at the robot locations and their relative
positions concerning the centroid. Rather than focusing on individual robots,
we focus the analysis on the density of robots per unit area to guarantee a
more resilient swarm, i.e., the functionality remains even if individuals go
missing or are misplaced during the mission. We reinforce the robustness of the
algorithm by providing sufficient conditions for the swarm shape so that the
ascending direction is almost parallel to the gradient. The swarm can respond
to an unexpected environment by morphing its shape and exploiting the existence
of multiple ascending directions. Finally, we validate our approach numerically
with hundreds of robots. The fact that a large number of robots always
calculate an ascending direction compensates for the loss of individuals and
mitigates issues arising from the actuator and sensor noises.Comment: 7 pages, submitted to ICRA 202
An Overview of Recent Progress in the Study of Distributed Multi-agent Coordination
This article reviews some main results and progress in distributed
multi-agent coordination, focusing on papers published in major control systems
and robotics journals since 2006. Distributed coordination of multiple
vehicles, including unmanned aerial vehicles, unmanned ground vehicles and
unmanned underwater vehicles, has been a very active research subject studied
extensively by the systems and control community. The recent results in this
area are categorized into several directions, such as consensus, formation
control, optimization, task assignment, and estimation. After the review, a
short discussion section is included to summarize the existing research and to
propose several promising research directions along with some open problems
that are deemed important for further investigations
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