Flocking small smart machines: An experiment in cooperative, multi-machine control

Klarer, Paul R.

doi:10.2172/573344

Cited by 7 publications

(6 citation statements)

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“…In much of the literature, the human is fed back information about the state of the robot team through the visual channel [5], [6], [7], [8], [9]. In [10], the visual feedback is combined with audio feedback in order to allow the user to gather more information about the group of robots at any instant.…”

Section: Introductionmentioning

confidence: 99%

Team-level properties for haptic human-swarm interactions

Setter

Kawashima

Egerstedt

2015

2015 American Control Conference (ACC)

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This paper explores how haptic interfaces should be designed to enable effective human-swarm interactions. When a single operator is interacting with a team of mobile robots, there are certain properties of the team that may help the operator complete the task at hand if these properties were fed back via haptics. However, not all team-level properties may be particularly well-suited for haptic feedback. In this paper, characteristics that make a property of a multi-agent system appropriate for haptic feedback are defined. The focus here is on leader-follower networks, in which one robot, the socalled leader, is controlled via an operator with a haptic device, whereas the remaining robots, the so-called followers, are tasked with maintaining distances between one another. Multi-agent manipulability, a property which describes how effective the leader is at controlling the movement of the followers, is proposed as one such appropriate property for haptic feedback in a human-swarm interaction scenario. Manipulability feedback is implemented using a PHANTOM Omni haptic joystick and experiments in which a team of mobile robots is controlled via a human operator with access to this feedback show that this is viable in practice.

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Section: Introductionmentioning

confidence: 99%

Team-level properties for haptic human-swarm interactions

Setter

Kawashima

Egerstedt

2015

2015 American Control Conference (ACC)

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“…The extant literature on HSI [8], [9], [10], [11], [12], [13], [14], [15], [16] have not studied the performance and behavior of human operators in the presence of delayed information transmission between the swarm and the human and vice versa (exceptions being [17], [18], [19], [20] for haptic control). In the haptic control studies, the operator uses a force feedback and (possibly) visual information about the robot state to apply a continuous control input and maintain a robot formation.…”

Section: Introductionmentioning

confidence: 99%

Neglect benevolence in human control of swarms in the presence of latency

Walker

Nunnally

Lewis

et al. 2012

2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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Autonomous swarm algorithms have been studied extensively in the past several years. However, there is little research on the effect of injecting human influence into a robot swarm-whether it be to update the swarm's current goals or reshape swarm behavior. While there has been growing research in the field of human-swarm interaction (HSI), no previous studies have investigated how humans interact with swarms under communication latency. We investigate the effects of latency both with and without a predictive display in a basic swarm foraging task to see if such a display can help mitigate the effects of delayed feedback of the swarm state. Furthermore, we introduce a new concept called neglect benevolence to represent how a human operator may need to give time for swarm algorithms to stabilize before issuing new commands, and we investigate it with respect to task performance. Our study shows that latency did affect a user's ability to control a swarm to find targets in the foraging task, and that the predictive display helped to remove these effects. We also found evidence for neglect benevolence, and that operators exploited neglect benevolence in different ways, leading to two different, but equally successful strategies in the target-searching task.

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“…Few studies show results of user studies and only show a proof of concept with a few real robots [9], [1]. Others have built theories and models around a hybrid system requiring a human operator and autonomous algorithm to show the *This research has been sponsored in part by AFOSR FA955008-10356 and ONR Grant N0001409-10680 downfalls and design challenges that must be considered when creating new control laws for HSI [10], [1], [11].…”

Section: Introductionmentioning

confidence: 99%

Using Coverage for Measuring the Effect of Haptic Feedback in Human Robotic Swarm Interaction

Nunnally

Walker

Chakraborty

et al. 2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

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Abstract-A robotic swarm is a decentralized group of robots which overcome failure of individual robots with robust emergent behaviors based on local interactions. These behaviors are not well built for accomplishing complex tasks, however, because of the changing assumptions required in various applications and environments. A new movement in the research field is to add human input to influence the swarm in order to help make the robots goal directed and overcome these problems. This research in Human Swarm Interaction (HSI) focuses on different control laws and ways to integrate the human intent with local control laws of the robots. Previous studies have all used visual feedback through a computer interface to give the user the swarm state information. This study shows the benefits of giving the operator haptic feedback as well along with the visual feedback in a target searching class. Researchers in multi-robot systems have shown benefits of haptic feedback in obstacle navigation before, but this study is a novel method because of the decentralized formation of the robotic swarm. In most environments, operators were able to cover significantly more area, increasing the chance of finding more targets. The other environment found no significant difference, showing that the haptic feedback does not degrade performance in any of the tested environments. This supports our hypothesis that haptic feedback is useful in HSI and requires further research to maximize its potential.

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Flocking small smart machines: An experiment in cooperative, multi-machine control

Cited by 7 publications

References 0 publications

Team-level properties for haptic human-swarm interactions

Team-level properties for haptic human-swarm interactions

Neglect benevolence in human control of swarms in the presence of latency

Using Coverage for Measuring the Effect of Haptic Feedback in Human Robotic Swarm Interaction

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