Force-Stiffness Feedback in Uninhabited Aerial Vehicle Teleoperation with Time Delay

Lam, T.M.; Mulder, Max; Mulder, J.A.; Helm, Frans C. van der

doi:10.2514/1.40191

Cited by 16 publications

(19 citation statements)

References 15 publications

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“…Clearly, more insight needs to be gained into how the various tuning parameters of the haptic feedback, including those related to the AFF as discussed in this paper, have an effect on operator performance, situation awareness, control activity, and workload. Preliminary studies have indicated that the PRF described in this paper indeed performed very well [27], [28], [41].…”

Section: Recommendationsmentioning

confidence: 61%

“…The proper tuning of the haptic "display" is a difficult problem. With operators holding the control manipulator, the effects of the haptic feedback depend on the neuromuscular system dynamics, which are likely to include adaptive reflexive behavior [28], [35]- [38]. For instance, the neuromuscular stiffness is not fixed but changes due to the settings of the reflexive feedback gains, the characteristics of which, in turn, depend on, among others, the task being conducted, and the bandwidth of external disturbances [39], [40].…”

Section: Recommendationsmentioning

confidence: 99%

“…At this stage of the project, the following is further assumed: 1) The helicopter only moves in the horizontal plane; 2) the UAV dynamics are those of a control-augmented "pilotfriendly" helicopter [26]; and 3) the dynamics are identical in every direction, with a constant deceleration limit. Furthermore, the effects of transmission delays that are common in teleoperation are neglected; these are treated in detail in our prior work [27], [28].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Artificial Force Field for Haptic Feedback in UAV Teleoperation

Lam¹,

Boschloo²,

Mulder³

et al. 2009

IEEE Trans. Syst., Man, Cybern. A

Self Cite

155

110

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Abstract-The feedback upon which operators in teleoperation tasks base their control actions differs substantially from the feedback to the driver of a vehicle. On the one hand, there is often a lack of sensory information; on the other hand, there is additional status information presented via the visual channel. Haptic feedback could be used to unload the visual channel and to compensate for the lack of feedback in other modalities. For collision avoidance, haptic feedback could provide repulsive forces via the control inceptor. Haptic feedback allows operators to interpret the repulsive forces as impedance to their control deflections when a potential for collision exists. Haptic information can be generated from an artificial force field (AFF) that maps environment constraints to repulsive forces. This paper describes the design and theoretical evaluation of a novel AFF, i.e., the parametric risk field, for teleoperation of an uninhabited aerial vehicle (UAV). The field allows adjustments of the size, shape, and force gradient by means of parameter settings, which determine the sensitivity of the field. Computer simulations were conducted to evaluate the effectiveness of the field for collision avoidance for various parameter settings. Results indicate that the novel AFF more effectively performs the collision avoidance function than potential fields known from literature. Because of its smaller size, the field yields lower repulsive forces, results in less force cancellation effects, and allows for larger UAV velocities. This indicates less operator control demand and more effective UAV operations, both expected to lead to lower operator workload, while, at the same time, increasing safety.

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Section: Recommendationsmentioning

confidence: 61%

Section: Recommendationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Artificial Force Field for Haptic Feedback in UAV Teleoperation

Lam¹,

Boschloo²,

Mulder³

et al. 2009

IEEE Trans. Syst., Man, Cybern. A

Self Cite

155

110

View full text Add to dashboard Cite

show abstract

“…There are only a few studies that have evaluated neuromuscular feedback in the design of a haptic shared control system: only for car-following (Abbink, 2006) and for unmanned aerial vehicle control (Lam et al, 2009). Unsupported manual control has received slightly more interest: for example, neuromuscular models and measurements have been developed for side-stick control for aircraft (Van Paassen, 1995), gas pedal control (Abbink, 2007) and steering (Pick & Cole, 2007;Pick & Cole, 2008) for automobiles.…”

Section: Introductionmentioning

confidence: 99%

Neuromuscular Analysis as a Guideline in designing Shared Control

Abbink¹,

Mulder²

2010

Advances in Haptics

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“…Albaker and Rahim [5] conducted a thorough survey of collision avoidance methods for UAS. The most common collision avoidance methods are geometric-based guidance methods [6][7][8][9][10][11][12][13], potential field methods [14,15], sampling-based methods [16,17], cell decomposition techniques, and graph-search algorithms [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Path Planning in the Local-Level Frame for Small Unmanned Aircraft Systems

Sahawneh¹,

Beard²

2017

Kinematics

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In this chapter, we propose a 3D path planning algorithm for small unmanned aircraft systems (UASs). We develop the path planning logic using a body fixed relative coordinate system which is the unrolled, unpitched body frame. In this relative coordinate system, the ownship is fixed at the center of the coordinate system, and the detected intruder is located at a relative position and moves with a relative velocity with respect to the ownship. This technique eliminates the need to translate the sensor's measurements from local coordinates to global coordinates, which saves computation cost and removes the error introduced by the transformation. We demonstrate and validate this approach using predesigned encounter scenarios in the Matlab/Simulink environment.

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Force-Stiffness Feedback in Uninhabited Aerial Vehicle Teleoperation with Time Delay

Cited by 16 publications

References 15 publications

Artificial Force Field for Haptic Feedback in UAV Teleoperation

Artificial Force Field for Haptic Feedback in UAV Teleoperation

Neuromuscular Analysis as a Guideline in designing Shared Control

Path Planning in the Local-Level Frame for Small Unmanned Aircraft Systems

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