Team-level properties for haptic human-swarm interactions

Setter, Tina; Kawashima, Hiroyuki; Egerstedt, Magnus

doi:10.1109/acc.2015.7170777

Cited by 11 publications

(11 citation statements)

References 22 publications

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“…In their article, Setter and al. [37] based on the haptic in order to get feedback about the swarm of mobile robots. The swarm used is made up of a leading robot and other followers robots that maintain a given formation.…”

Section: Become the Leadermentioning

confidence: 99%

Human-Rover Interactions and Swarm Algorithms of Mobile Robots in an Open and Crowded Environment: A Survey

Vaidis¹,

Otis²

2020

Preprint

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As a result of extensive research in the field of mobile robots (rovers) and swarms, a number of algorithms exist to assist them for executing a mission in the three levels of software architecture: strategic (interaction loop level), tactic (planning) and operational (sensing, control and actuation). They allow them to achieve their goals while adapting to their environment through a multitude of methods designed for each situation. For this reason, a literature review of the latest research conducted in previous years is required to identify new research trends in human-swarm interaction applied to help humans in hazardous environment such as militarized zone. In this paper, we will present some interesting algorithms for interactive and autonomous mobile robots acting in swarms in an open and crowded environment. A discussion will focus on comparing different algorithms and their advantages and disadvantages.

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Section: Become the Leadermentioning

confidence: 99%

Human-Rover Interactions and Swarm Algorithms of Mobile Robots in an Open and Crowded Environment: A Survey

Vaidis¹,

Otis²

2020

Preprint

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“…Other studies have shown that small teams of robots have benefited from using haptic feedback in methods of controlling a group of UAVs in a cluttered environment [27], and conveying a sense of team-level properties such as manipulability [17]. Overall, the potential for using haptic feedback to control a robot team, maintain awareness of primary tasks and respond to secondary tasks, demands further research.…”

Section: Haptic Feedbackmentioning

confidence: 99%

“…The operator's ability to multi-task could be improved with the use of a multimodal interface, using both visual and haptic feedback. Haptic feedback has been shown to reduce collisions when piloting individual robotic vehicles [13,14], and provide a sense of team-level properties when teleoperating multiple robots [15][16][17]. There are, however, possible drawbacks to using haptic feedback, as it has been shown to increase operator workload in some studies [18,19].…”

Section: Introductionmentioning

confidence: 99%

Haptic Shape-Based Management of Robot Teams in Cordon and Patrol

McDonald

Colton

Alder

et al. 2017

Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction

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There are many current and future scenarios that require teams of air, ground or humanoid robots to gather information in complex and often dangerous environments, where it would be unreasonable or impossible for humans to be physically present [1-6]. The current state of the art involves a single robot being monitored by one or many human operators [7], but a single operator managing a team of autonomous robots is preferred as long as effective and time-efficient management of the team is maintained [8, 9]. This is limited by the operator's ability to command actions of multiple robots, be aware of robot states, and respond to less important tasks, while accomplishing a primary objective defined by the application scenario. The operator's ability to multi-task could be improved with the use of a multimodal interface, using both visual and haptic feedback. This thesis investigates the use of haptic feedback in developing intuitive, shape-based interaction to maintain heads-up control and increase an operator's situation awareness (SA) while managing a robot team. In this work, the autonomous behavior of the team is modeled after a patrol and cordon scenario, where the team travels to and surrounds buildings of interest. A novel approach that involves treating the team as a moldable volume is presented, where deformations of this volume correspond to changes in team shape. During surround mode, the operator may explore or manipulate the team shape to create custom formations around a building. A spacing interaction method also allows the operator to adjust how robots are spaced within the current shape. Separate haptic feedback is developed for each method to allow the operator to "feel" the shape or spacing manipulation. During travel mode, the operator chooses desired travel locations and receives feedback to help identify how and where the team travels. RoTHSim, an experimental robot team haptic simulator, was developed and used as a test bed for single-operator management of a robot team in a multitasking reconnaissance and surveillance scenario. Using RoTHSim, a human subject experiment was conducted with 19 subjects to determine the effects of haptic feedback and task demand difficulty on levels of performance, SA and workload. Results from the experiment suggest that haptic feedback significantly improves operator performance in a reconnaissance task when task demand is higher, but may slightly increase operator workload. Due to the experimental setup, these results suggest that haptic feedback may make it easier for the operator to experience heads-up control of a team of autonomous robots. There were no significance differences on SA scores due to haptic feedback in this study.

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“…In a similar scenario, the human directly controls the object position (i.e. the mean position of the robots here) and formation control is performed autonomously in [18], [102], [98]. In [81] both subtasks are performed by the human.…”

Section: Global and Local Behaviorsmentioning

confidence: 99%

“…The interaction of the human with individual robots limits the number of robots within the team as it imposes workload and time-related stress on the human operator [75], [113]. As an alternative the human interacts only through a single leader robot with the team reducing the human workload considerably [98]. In this case the human is required to have a very good understanding of the autonomous team behavior in order to efficiently perform tasks.…”

Section: Shared Control For Human-robot Teamsmentioning

confidence: 99%

Control sharing in human-robot team interaction

Musić

Hirche

2017

Annual Reviews in Control

123

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The interaction between humans and robot teams is highly relevant in many application domains, for example in collaborative manufacturing, search and rescue, and logistics. It is well-known that humans and robots have complementary capabilities: Humans are excellent in reasoning and planning in unstructured environments, while robots are very good in performing tasks repetitively and precisely. In consequence, one of the key research questions is how to combine human and robot team decision making and task execution capabilities in order to exploit their complementary skills. From a controls perspective this question boils down to how control should be shared among them. This article surveys advances in humanrobot team interaction with special attention devoted to control sharing methodologies. Additionally, aspects affecting the control sharing design, such as human behavior modeling, level of autonomy and humanmachine interfaces are identified. Open problems and future research directions towards joint decision making and task execution in human-robot teams are discussed.

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Team-level properties for haptic human-swarm interactions

Cited by 11 publications

References 22 publications

Human-Rover Interactions and Swarm Algorithms of Mobile Robots in an Open and Crowded Environment: A Survey

Human-Rover Interactions and Swarm Algorithms of Mobile Robots in an Open and Crowded Environment: A Survey

Haptic Shape-Based Management of Robot Teams in Cordon and Patrol

Control sharing in human-robot team interaction

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