“…In these types of behaviours, human behaviour has been likened to that of a servomechanism or controller (Wiener 1948), and since the 1940s, many mathematical models of human sensorimotor control behaviour have been proposed based on the continuous, linear feedback mechanisms of classical engineering control theory (e.g. Tustin 1947; McRuer et al. 1965; Nashner 1972; Robinson et al.…”
Section: Introductionmentioning
confidence: 99%
“…(1970), features forward and inverse models, and includes provisions allowing for both a minimum refractory period and error deadzones.Fig. 1An early observation of intermittent-looking control by Tustin (1947). The plot is of the operator handle position in a gun turret aiming task.…”
Section: Introductionmentioning
confidence: 99%
“…An early observation of intermittent-looking control by Tustin (1947). The plot is of the operator handle position in a gun turret aiming task.…”
A conceptual and computational framework is proposed for modelling of human sensorimotor control and is exemplified for the sensorimotor task of steering a car. The framework emphasises control intermittency and extends on existing models by suggesting that the nervous system implements intermittent control using a combination of (1) motor primitives, (2) prediction of sensory outcomes of motor actions, and (3) evidence accumulation of prediction errors. It is shown that approximate but useful sensory predictions in the intermittent control context can be constructed without detailed forward models, as a superposition of simple prediction primitives, resembling neurobiologically observed corollary discharges. The proposed mathematical framework allows straightforward extension to intermittent behaviour from existing one-dimensional continuous models in the linear control and ecological psychology traditions. Empirical data from a driving simulator are used in model-fitting analyses to test some of the framework’s main theoretical predictions: it is shown that human steering control, in routine lane-keeping and in a demanding near-limit task, is better described as a sequence of discrete stepwise control adjustments, than as continuous control. Results on the possible roles of sensory prediction in control adjustment amplitudes, and of evidence accumulation mechanisms in control onset timing, show trends that match the theoretical predictions; these warrant further investigation. The results for the accumulation-based model align with other recent literature, in a possibly converging case against the type of threshold mechanisms that are often assumed in existing models of intermittent control.
“…In these types of behaviours, human behaviour has been likened to that of a servomechanism or controller (Wiener 1948), and since the 1940s, many mathematical models of human sensorimotor control behaviour have been proposed based on the continuous, linear feedback mechanisms of classical engineering control theory (e.g. Tustin 1947; McRuer et al. 1965; Nashner 1972; Robinson et al.…”
Section: Introductionmentioning
confidence: 99%
“…(1970), features forward and inverse models, and includes provisions allowing for both a minimum refractory period and error deadzones.Fig. 1An early observation of intermittent-looking control by Tustin (1947). The plot is of the operator handle position in a gun turret aiming task.…”
Section: Introductionmentioning
confidence: 99%
“…An early observation of intermittent-looking control by Tustin (1947). The plot is of the operator handle position in a gun turret aiming task.…”
A conceptual and computational framework is proposed for modelling of human sensorimotor control and is exemplified for the sensorimotor task of steering a car. The framework emphasises control intermittency and extends on existing models by suggesting that the nervous system implements intermittent control using a combination of (1) motor primitives, (2) prediction of sensory outcomes of motor actions, and (3) evidence accumulation of prediction errors. It is shown that approximate but useful sensory predictions in the intermittent control context can be constructed without detailed forward models, as a superposition of simple prediction primitives, resembling neurobiologically observed corollary discharges. The proposed mathematical framework allows straightforward extension to intermittent behaviour from existing one-dimensional continuous models in the linear control and ecological psychology traditions. Empirical data from a driving simulator are used in model-fitting analyses to test some of the framework’s main theoretical predictions: it is shown that human steering control, in routine lane-keeping and in a demanding near-limit task, is better described as a sequence of discrete stepwise control adjustments, than as continuous control. Results on the possible roles of sensory prediction in control adjustment amplitudes, and of evidence accumulation mechanisms in control onset timing, show trends that match the theoretical predictions; these warrant further investigation. The results for the accumulation-based model align with other recent literature, in a possibly converging case against the type of threshold mechanisms that are often assumed in existing models of intermittent control.
“…The theory of human control behavior goes back to the 1930–40s, when Tustin characterized the human as a feedback servo element (Tustin, 1947). The feedback theory was soon applied to modeling pilot/vehicle system.…”
Modeling agile and versatile spatial behavior remains a challenging task, due to the intricate coupling of planning, control, and perceptual processes. Previous results have shown that humans plan and organize their guidance behavior by exploiting patterns in the interactions between agent or organism and the environment. These patterns, described under the concept of Interaction Patterns (IPs), capture invariants arising from equivalences and symmetries in the interaction with the environment, as well as effects arising from intrinsic properties of human control and guidance processes, such as perceptual guidance mechanisms. The paper takes a systems' perspective, considering the IP as a unit of organization, and builds on its properties to present a hierarchical model that delineates the planning, control, and perceptual processes and their integration. The model's planning process is further elaborated by showing that the IP can be abstracted, using spatial time-to-go functions. The perceptual processes are elaborated from the hierarchical model. The paper provides experimental support for the model's ability to predict the spatial organization of behavior and the perceptual processes.
“…It is said that Tustin tried first to express a human control model in 1 940s when classic control theories were systematized. He utilized a linear transfer function to model a human action and proposed linear servo control [2]. In the 1960's, many models to express human control properties were introduced.…”
Human Adaptive Mechatronics(HAM) is an intelligent mechanical system that adapts themselves to human skill under various environments, improves human skill, and assists the operation to achieve best performance of the human-machine system. In this new kind of human-machine system, human factor has to be taken into consideration for the motion-control design. In this paper, several topics of system theories that focus attention on the relation between human and machine are presented.ke~ywords: Human Adaptive Mechatronics, skill, brain monitoring, safe manual control, intermittency control, variable dynamics assist-control.
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