51,208 research outputs found
Optimality Principles and Motion Planning of Human-Like Reaching Movements
The paper deals with modeling of human-like reaching movements. Several issues are under study. First, we consider a model of unconstrained reaching movements that corresponds to the minimization of control effort. It is shown that this model can be represented by the wellknown Beta function. The representation can be used for the construction of fractional order models and also for modeling of asymmetric velocity proï¬les. Next, we address the formation of boundary conditions in a natural way. From the mathematical point of view, the structure of the optimal solution is deï¬ned not only by the form of the optimality criterion but also by the boundary conditions of the optimization task. The natural boundary conditions, deï¬ned in this part of the paper, can also be used in modeling asymmetric velocity proï¬les. Finally, addressing the modeling of reaching movements with bounded control actions, we consider the minimum time formulation of the optimization problem and (for the n-th order integrator) ï¬nd its analytical solution
A Computational Approach for Human-like Motion Generation in Upper Limb Exoskeletons Supporting Scapulohumeral Rhythms
This paper proposes a computational approach for generation of reference path
for upper-limb exoskeletons considering the scapulohumeral rhythms of the
shoulder. The proposed method can be used in upper-limb exoskeletons with 3
Degrees of Freedom (DoF) in shoulder and 1 DoF in elbow, which are capable of
supporting shoulder girdle. The developed computational method is based on
Central Nervous System (CNS) governing rules. Existing computational reference
generation methods are based on the assumption of fixed shoulder center during
motions. This assumption can be considered valid for reaching movements with
limited range of motion (RoM). However, most upper limb motions such as
Activities of Daily Living (ADL) include large scale inward and outward
reaching motions, during which the center of shoulder joint moves
significantly. The proposed method generates the reference motion based on a
simple model of human arm and a transformation can be used to map the developed
motion for other exoskeleton with different kinematics. Comparison of the model
outputs with experimental results of healthy subjects performing ADL, show that
the proposed model is able to reproduce human-like motions.Comment: In 2017 IEEE International Symposium on Wearable & Rehabilitation
Robotics (WeRob2017
Task-demands can immediately reverse the effects of sensory-driven saliency in complex visual stimuli
In natural vision both stimulus features and task-demands affect an observer's attention. However, the relationship between sensory-driven (“bottom-up”) and task-dependent (“top-down”) factors remains controversial: Can task-demands counteract strong sensory signals fully, quickly, and irrespective of bottom-up features? To measure attention under naturalistic conditions, we recorded eye-movements in human observers, while they viewed photographs of outdoor scenes. In the first experiment, smooth modulations of contrast biased the stimuli's sensory-driven saliency towards one side. In free-viewing, observers' eye-positions were immediately biased toward the high-contrast, i.e., high-saliency, side. However, this sensory-driven bias disappeared entirely when observers searched for a bull's-eye target embedded with equal probability to either side of the stimulus. When the target always occurred in the low-contrast side, observers' eye-positions were immediately biased towards this low-saliency side, i.e., the sensory-driven bias reversed. Hence, task-demands do not only override sensory-driven saliency but also actively countermand it. In a second experiment, a 5-Hz flicker replaced the contrast gradient. Whereas the bias was less persistent in free viewing, the overriding and reversal took longer to deploy. Hence, insufficient sensory-driven saliency cannot account for the bias reversal. In a third experiment, subjects searched for a spot of locally increased contrast (“oddity”) instead of the bull's-eye (“template”). In contrast to the other conditions, a slight sensory-driven free-viewing bias prevails in this condition. In a fourth experiment, we demonstrate that at known locations template targets are detected faster than oddity targets, suggesting that the former induce a stronger top-down drive when used as search targets. Taken together, task-demands can override sensory-driven saliency in complex visual stimuli almost immediately, and the extent of overriding depends on the search target and the overridden feature, but not on the latter's free-viewing saliency
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Incorporating Human Beliefs and Behaviors into Wildlife Ecology
Like much of the global biosphere, wildlife species have experienced rapid declines during the Anthropocene. Wildlife ecologists have responded to these crises by developing a range of technologies, techniques, and large datasets, which together have revolutionized the field, provided novel insights into the movements and behaviors of animals, and identified new risks and impacts to wildlife in a human-dominated world. While these advances have been vitally important, wildlife ecology has been slower to recognize and incorporate humans themselves into its new research domains. The chapters of this dissertation explore methods for better incorporating human behaviors, beliefs, actions, and infrastructure into the theories and approaches in wildlife ecology that have flourished in the last two decades. The research presented here demonstrates the importance of linking human beliefs and behaviors to wildlife ecology both by presenting novel findings and by showing the opportunities missed when narrow approaches are applied to complex socio-ecological problems.In Chapter 1, I provide a general introduction on the theories underlying this research, contextualize the research questions in light of the loss and recovery of large predators, and describe the research site where I collected much of the data for this dissertation. In Chapter 2, I apply the methods of movement ecology to some of the first fine-scale telemetry data collected on rifle hunters. I draw conclusions about their individual, site-level, and regional-level hunting behaviors and discuss the broad implications of these findings for hunting management. In Chapter 3, I examine livestock-predator conflict using approaches from both ecology and the social sciences. I describe a form of selection bias that is likely widespread but unreported due to the omission of social data from ecological models of conflict, and I offer guidelines for combining and translating ecological and social research on conflict. In Chapter 4, I explore the ecological impacts of one of the most globally widespread human constructions, the fence. I show for the first time the potential extent of fencing at large scales and discuss the wide variety of ecological effects of fences for both humans and ecosystems. I further highlight biases and gaps in fence research that have thus far limited a complete understanding of the environmental effects of these features. In Chapter 5, I conclude by making recommendations regarding how research might better incorporate human perceptions, decisions, and actions into ecology
How simple rules determine pedestrian behavior and crowd disasters
With the increasing size and frequency of mass events, the study of crowd
disasters and the simulation of pedestrian flows have become important research
areas. Yet, even successful modeling approaches such as those inspired by
Newtonian force models are still not fully consistent with empirical
observations and are sometimes hard to calibrate. Here, a novel cognitive
science approach is proposed, which is based on behavioral heuristics. We
suggest that, guided by visual information, namely the distance of obstructions
in candidate lines of sight, pedestrians apply two simple cognitive procedures
to adapt their walking speeds and directions. While simpler than previous
approaches, this model predicts individual trajectories and collective patterns
of motion in good quantitative agreement with a large variety of empirical and
experimental data. This includes the emergence of self-organization phenomena,
such as the spontaneous formation of unidirectional lanes or stop-and-go waves.
Moreover, the combination of pedestrian heuristics with body collisions
generates crowd turbulence at extreme densities-a phenomenon that has been
observed during recent crowd disasters. By proposing an integrated treatment of
simultaneous interactions between multiple individuals, our approach overcomes
limitations of current physics-inspired pair interaction models. Understanding
crowd dynamics through cognitive heuristics is therefore not only crucial for a
better preparation of safe mass events. It also clears the way for a more
realistic modeling of collective social behaviors, in particular of human
crowds and biological swarms. Furthermore, our behavioral heuristics may serve
to improve the navigation of autonomous robots.Comment: Article accepted for publication in PNA
Dynamics of Current, Charge and Mass
Electricity plays a special role in our lives and life. Equations of electron
dynamics are nearly exact and apply from nuclear particles to stars. These
Maxwell equations include a special term the displacement current (of vacuum).
Displacement current allows electrical signals to propagate through space.
Displacement current guarantees that current is exactly conserved from inside
atoms to between stars, as long as current is defined as Maxwell did, as the
entire source of the curl of the magnetic field. We show how the Bohm
formulation of quantum mechanics allows easy definition of current. We show how
conservation of current can be derived without mention of the polarization or
dielectric properties of matter. Matter does not behave the way physicists of
the 1800's thought it does with a single dielectric constant, a real positive
number independent of everything. Charge moves in enormously complicated ways
that cannot be described in that way, when studied on time scales important
today for electronic technology and molecular biology. Life occurs in ionic
solutions in which charge moves in response to forces not mentioned or
described in the Maxwell equations, like convection and diffusion. Classical
derivations of conservation of current involve classical treatments of
dielectrics and polarization in nearly every textbook. Because real dielectrics
do not behave in a classical way, classical derivations of conservation of
current are often distrusted or even ignored. We show that current is conserved
exactly in any material no matter how complex the dielectric, polarization or
conduction currents are. We believe models, simulations, and computations
should conserve current on all scales, as accurately as possible, because
physics conserves current that way. We believe models will be much more
successful if they conserve current at every level of resolution, the way
physics does.Comment: Version 4 slight reformattin
The Complementary Brain: From Brain Dynamics To Conscious Experiences
How do our brains so effectively achieve adaptive behavior in a changing world? Evidence is reviewed that brains are organized into parallel processing streams with complementary properties. Hierarchical interactions within each stream and parallel interactions between streams create coherent behavioral representations that overcome the complementary deficiencies of each stream and support unitary conscious experiences. This perspective suggests how brain design reflects the organization of the physical world with which brains interact, and suggests an alternative to the computer metaphor suggesting that brains are organized into independent modules. Examples from perception, learning, cognition, and action are described, and theoretical concepts and mechanisms by which complementarity is accomplished are summarized.Defense Advanced Research Projects and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (ITI-97-20333); Office of Naval Research (N00014-95-1-0657
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