Past, present and future implications of human supervisory control in space missions

Sim, Liang; Cummings, Mary L.; Smith, Cristin A.

doi:10.1016/j.actaastro.2008.01.029

Cited by 24 publications

(10 citation statements)

References 14 publications

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“…It was introduced to minimize the computational burden of control and mitigate detrimental effects of time delays due to remote (tele-)operation [49] , [50] . It has been especially important in robotic space exploration [51] . Applied to human motor control, the key idea is that, because of the limited response speed of muscles and the substantial delays due to neural conduction, in effect the supra-spinal nervous system tele-operates the neuro-mechanical periphery .…”

Section: Discussionmentioning

confidence: 99%

Walking Is Not Like Reaching: Evidence from Periodic Mechanical Perturbations

Ahn

Hogan

2012

PLoS ONE

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The control architecture underlying human reaching has been established, at least in broad outline. However, despite extensive research, the control architecture underlying human locomotion remains unclear. Some studies show evidence of high-level control focused on lower-limb trajectories; others suggest that nonlinear oscillators such as lower-level rhythmic central pattern generators (CPGs) play a significant role. To resolve this ambiguity, we reasoned that if a nonlinear oscillator contributes to locomotor control, human walking should exhibit dynamic entrainment to periodic mechanical perturbation; entrainment is a distinctive behavior of nonlinear oscillators. Here we present the first behavioral evidence that nonlinear neuro-mechanical oscillators contribute to the production of human walking, albeit weakly. As unimpaired human subjects walked at constant speed, we applied periodic torque pulses to the ankle at periods different from their preferred cadence. The gait period of 18 out of 19 subjects entrained to this mechanical perturbation, converging to match that of the perturbation. Significantly, entrainment occurred only if the perturbation period was close to subjects' preferred walking cadence: it exhibited a narrow basin of entrainment. Further, regardless of the phase within the walking cycle at which perturbation was initiated, subjects' gait synchronized or phase-locked with the mechanical perturbation at a phase of gait where it assisted propulsion. These results were affected neither by auditory feedback nor by a distractor task. However, the convergence to phase-locking was slow. These characteristics indicate that nonlinear neuro-mechanical oscillators make at most a modest contribution to human walking. Our results suggest that human locomotor control is not organized as in reaching to meet a predominantly kinematic specification, but is hierarchically organized with a semi-autonomous peripheral oscillator operating under episodic supervisory control.

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Section: Discussionmentioning

confidence: 99%

Walking Is Not Like Reaching: Evidence from Periodic Mechanical Perturbations

Ahn

Hogan

2012

PLoS ONE

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“…AI changes goals set by the human and does something else. (Based on Sheraton and Verplank 1978, as adapted by Sim et al 2008, and by Dator 2012. Step 11 was added by Jerry Glenn on the APF list, March 22, 2019)…”

Section: A Possible Continuum Of Human–ai Interactionsmentioning

confidence: 99%

Editorial: Thoughts on Big Data, AI, and Futures Studies

Dator¹

2020

World Futures Review

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“…Unmanned spacecraft often have a similar or even higher level of automation as compared to modern UVs, and there are some similarities between the two domains, including the potential desire to use these vehicles for surveillance missions, the necessity of an algorithm to coordinate the movement of the vehicles, and the human-computer interaction necessary for mission success. Although some studies have considered the role of the human controller in supervising multiple spacecraft or other space autonomous agents [39][40][41][42][43][44], few have live experiments with human operators to investigate the most appropriate way for operators to interact with or modify these control algorithms in real-time operations, thus warranting further research in this important area.…”

Section: Introductionmentioning

confidence: 99%

Operator Object Function Guidance for a Real-Time Unmanned Vehicle Scheduling Algorithm

Clare

Cummings

How

et al. 2012

Journal of Aerospace Computing, Information, and Communication

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Advances in autonomy have made it possible to invert the typical operator-to-unmanned-vehicle ratio so that a single operator can now control multiple heterogeneous unmanned vehicles. Algorithms used in unmanned-vehicle path planning and task allocation typically have an objective function that only takes into account variables initially identified by designers with set weightings. This can make the algorithm seemingly opaque to an operator and brittle under changing mission priorities. To address these issues, it is proposed that allowing operators to dynamically modify objective function weightings of an automated planner during a mission can have performance benefits. A multiple-unmanned-vehicle simulation test bed was modified so that operators could either choose one variable or choose any combination of equally weighted variables for the automated planner to use in evaluating mission plans. Results from a human-participant experiment showed that operators rated their performance and confidence highest when using the dynamic objective function with multiple objectives. Allowing operators to adjust multiple objectives resulted in enhanced situational awareness, increased spare mental capacity, fewer interventions to modify the objective function, and no significant differences in mission performance. Adding this form of flexibility and transparency to automation in future unmanned vehicle systems could improve performance, engender operator trust, and reduce errors.

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Past, present and future implications of human supervisory control in space missions

Cited by 24 publications

References 14 publications

Walking Is Not Like Reaching: Evidence from Periodic Mechanical Perturbations

Walking Is Not Like Reaching: Evidence from Periodic Mechanical Perturbations

Editorial: Thoughts on Big Data, AI, and Futures Studies

Operator Object Function Guidance for a Real-Time Unmanned Vehicle Scheduling Algorithm

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