Bilateral Teleoperation of Groups of Mobile Robots With Time-Varying Topology

Franchi, Antonio; Secchi, Cristian; Son, Hyoung Il; Bülthoff, HH; Giordano, Paolo Robuffo

doi:10.1109/tro.2012.2196304

Cited by 184 publications

(135 citation statements)

References 29 publications

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“…Unfortunately, (7) is not passive with respect to the pair (F h +F m , x m ) [14]. In order to preserve the passivity of the master, we pre-compensate the master using the technique proposed in [16] in order to make the master passive with respect to the pair (F h + F m , r m ) using the storage function…”

Section: Shared Teleoperation Architecturementioning

confidence: 99%

An assisted bilateral control strategy for 3D pose estimation of visual features

Battilani

Spica

Giordano

et al. 2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-Teleoperating a quadrotor equipped with a monocular camera for exploring a wide area in search of something has become a common practice in many application scenarios (e.g. search and rescue). In order to efficiently plan operations, estimating the 3D pose of a point of interest is as important as detecting it. In this paper we propose a novel bilateral teleoperation architecture where an estimation scheme is exploited for recovering the position of a set of visual features while an operator steers the motion of the quadrotor UAV. The operator acts on a force-feedback master device that produces force cues meant to suggest where to drive the quadrotor for improving the convergence rate of the estimation process. The effectiveness of the proposed teleoperation strategy is validated by means of hardware in the loop simulations.

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Section: Shared Teleoperation Architecturementioning

confidence: 99%

An assisted bilateral control strategy for 3D pose estimation of visual features

Battilani

Spica

Giordano

et al. 2017

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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“…Our simulation environment SSX has been successfully employed to validate several multi-robot control algorithms proposed in recent papers by some of the authors, see, e.g., [16][17][18] and http://www.youtube.com/user/MPIRobotics for the related video selection. In the majority of these works we also performed real-robot experiments using the same algorithms and we observed a remarkable similarity between simulative and experimental results.…”

Section: Validationmentioning

confidence: 99%

SwarmSimX: Real-Time Simulation Environment for Multi-robot Systems

Lächele

Franchi

Bülthoff

et al. 2012

Simulation, Modeling, and Programming for Autonomous Robots

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Abstract. In this paper we present a novel simulation environment called SwarmSimX with the ability to simulate dozens of robots in a realistic 3D environment. The software architecture of SwarmSimX allows new robots, sensors, and other libraries to be loaded at runtime, extending the functionality of the simulation environment significantly. In addition, SwarmSimX allows an easy exchange of the underlying libraries used for the visual and physical simulation to incorporate different libraries (e.g., improved or future versions). A major feature is also the possibility to perform the whole simulation in real-time allowing for human-in-the-loop or hardware-in-the-loop scenarios. SwarmSimX has been already employed in several works presenting haptic shared control of multiple mobile robots (e.g., quadrotor UAVs). Additionally, we present here two validation tests showing the physical fidelity and the real-time performance of SwarmSimX. For the tests we used NVIDIA R PhysX R and Ogre3D as physics and rendering libraries, respectively.

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“…This formation control was coupled with autonomous decisions to split and join around obstacles in the path of the robots. Further publications showed that this control technique was successful with latency, and results were demonstrated both in simulation and with real hardware in three dimensions Franchi, Secchi, Son, et al, 2012; P. R. Giordano et al, 2013;Franchi, Secchi, Ryll, Bülthoff, & Giordano, 2012;Franchi, Masone, et al, 2012;Lee, Franchi, Son, Bülthoff, & Giordano, 2013).…”

Section: Haptics In Human-robot Interactionmentioning

confidence: 96%

“…The group of robots maintain a rigid formation using a decentralized spring force control, while the operator controls the centroid of the agents to follow a predefined path around obstacles. Later work (Franchi, Secchi, Son, Bülthoff, & Giordano, 2012; P. R. Giordano et al, 2013) removed the rigid formation assumption and allowed for a looser formation control with links between robots allowed to be broken or established. This formation control was coupled with autonomous decisions to split and join around obstacles in the path of the robots.…”

Section: Haptics In Human-robot Interactionmentioning

confidence: 99%

“…In (Franchi, Secchi, Son, et al, 2012), the authors propose a bilateral teleoperation system with haptic feedback to allow a human operator to control a heterogeneous team of robots in a variety of settings. The authors use a leader-follower paradigm and demonstrate their results with a single leader controlling up to eight robots.…”

Section: Haptics In Human-robot Interactionmentioning

confidence: 99%

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Using Haptic Feedback in Human-Swarm Interaction

Nunnally

Walker

Lewis

et al.

Handbook of Research on Design, Control, and Modeling of Swarm Robotics

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A swarm of robots is a large group of individual agents that autonomously coordinate via local control laws. Their emergent behavior allows simple robots to accomplish complex tasks. Since missions may have complex objectives that change dynamically due to environmental and mission changes, human control and influence over the swarm is needed. The field of Human Swarm Interaction (HSI) is young, with few user studies, and even fewer papers focusing on giving non-visual feedback to the operator. The authors will herein present a background of haptics in robotics and swarms and two studies that explore various conditions under which haptic feedback may be useful in HSI. The overall goal of the studies is to explore the effectiveness of haptic feedback in the presence of other visual stimuli about the swarm system. The findings show that giving feedback about nearby obstacles using a haptic device can improve performance, and that a combination of feedback from obstacle forces via the visual and haptic channels provide the best performance.

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Bilateral Teleoperation of Groups of Mobile Robots With Time-Varying Topology

Cited by 184 publications

References 29 publications

An assisted bilateral control strategy for 3D pose estimation of visual features

An assisted bilateral control strategy for 3D pose estimation of visual features

SwarmSimX: Real-Time Simulation Environment for Multi-robot Systems

Using Haptic Feedback in Human-Swarm Interaction

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