Conference Paper

Entrapment/escorting and patrolling missions in multi-robot cluster space control

Robotic Syst. Lab., Santa Clara Univ., Santa Clara, CA, USA
DOI: 10.1109/IROS.2009.5354815 Conference: Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on
Source: IEEE Xplore


The tasks of entrapping/escorting and patrolling around an autonomous target are presented making use of the multi-robot cluster space control approach. The cluster space control technique promotes simplified specification and monitoring of the motion of mobile multi-robot systems of limited size. Previous work has established the conceptual foundation of this approach and has experimentally verified and validated its use for 2-robot, 3-robot and 4-robot systems, with varying implementations ranging from automated trajectory control to human-in-the-loop piloting. In this publication, we show that the problem of entrapping/escorting/patrolling is trivial to define and manage from a cluster space perspective. Using a 3-robot experimental testbed, results are shown for the given tasks. We also revise the definition of the cluster space framework for a three-robot formation and incorporate a robot-level obstacle avoidance functionality.

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Available from: Jose Acain, Nov 18, 2014
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    • "Other applications may require even more integrated operation and relative position control, such as proposed sparse array space telescopes [8]. Our work focused on the highly integrated end of the control spectrum, with target applications that include active escorting/guarding [9], [10], object tracking, object manipulation [11], and sparse antenna arrays [12]. Given that these applications require active control of the relative spatial characteristics of the robot formation, we have developed a flexible and powerful formation-level control architecture, known as the cluster space formation control technique [13], which provides a suitable level of abstraction at the application-formation control interface. "
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    ABSTRACT: This paper presents an experimentally demonstrated gradient-based multirobot technique for adaptively navigating within a parameter field. To implement this technique, simultaneous measurements of the parameter are made at different locations within the field by a spatially controlled cluster of mobile robots. These measurements are shared in order to compute a local gradient of the field. Depending on the task to be achieved, the multirobot cluster is directed with respect to this direction. Moving in or opposite to the gradient direction allows efficient navigation to local maxima/minima in the field, a capability of interest for applications such as detecting pollution sources or the location of resource-starved areas. Moving perpendicular to the gradient direction allows parameter contours to be navigated, a behavior useful for applications such as defining the extent of a field or establishing a safety perimeter at a defined field level. This paper describes the multirobot control technique which combines a full degree-of-freedom "cluster space" multirobot controller with a gradient-based adaptive navigation capability. Verification of the technique through field experiments using a fleet of three robotic kayaks is also presented. Finally, a discussion of results, a review of challenges, and a review of ongoing and future work are presented.
    Full-text · Article · Apr 2015 · IEEE/ASME Transactions on Mechatronics
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    • "To date, we have successfully implemented cluster space control in experiments with clusters of up to 6 vehicles, for both holonomic and nonholonomic robots, for robots negotiating obstacle fields, for piloted and supervisory control modes, and for a variety of relative/absolute positioning and tracking pose sensing systems. The guarding/shielding application reported here is an extension of our previous work in escorting/patrolling [28]-[30]. In addition, we are applying the control strategy to other applications such as gradient-based environmental sensing [31]-[32] and reconfigurable sparse array communication systems [33]. "
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    ABSTRACT: There is often a need to mark or patrol marine areas in order to prevent boat traffic from approaching critical regions, such as the location of a high-value vessel, a dive site, or a fragile marine ecosystem. In this paper, we describe the use of a fleet of robotic kayaks that provides such a function: the fleet circumnavigates the critical area until a threatening boat approaches, at which point the fleet establishes a barrier between the ship and the protected area. Coordinated formation control of the fleet is implemented through the use of the cluster-space control architecture, which is a full-order controller that treats the fleet as a virtual, articulating, kinematic mechanism. An application-specific layer interacts with the cluster-space controller in order for an operator to directly specify and monitor guarding-related parameters, such as the spacing between boats. This system has been experimentally verified in the field with a fleet of robotic kayaks. In this paper, we describe the control architecture used to establish the guarding behavior, review the design of the robotic kayaks, and present experimental data regarding the functionality and performance of the system.
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    • "Many of the works concerning robot teams focus on the cooperative robot motion ([14], [15],[16]), but not on the interaction with the people. Some of these works propose escorting scenarios such as [17] or [18], but only from the multi-robot control point of view. In [19] an architecture for guiding a group of humans by a team of robots is introduced. "
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    ABSTRACT: In this paper we address robot-human interactions in a multi-robot and people group framework. The objective is to develop and evaluate techniques for missions in which several robots cooperate among themselves, interacting with a group of people. The robots detect people behaviors and act consequently adopting different strategies. Probabilistic techniques for robust cooperative detection of group and individual behavior are developed from the range finder information. Environment perception and cooperative motion planning techniques adaptable to the situation observed are developed and jointly used with the reactions to the people's behavior. In order to evaluate the system, we propose a scenario where the robots guide a group of people to a goal position. This scenario has been tested in simulations and in real experiments, to validate the techniques developed.
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