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This paper presents a hierarchical critic learning optimal control (H‐CLOC) strategy for a lower limb exoskeleton system with prescribed state constraints. The prescribed state constraints of the exoskeleton are mathematically modeled by means of a state error transition function, which transforms the constrained state into an equivalent new unconstrained state. A hierarchical framework including a high‐level motion trajectory planner and a low‐level critic learning (CL) controller is proposed for optimal control of the exoskeleton. The estimation of human motion intentions is achieved using dynamic movement primitives (DMPs), which are capable of accurately replicating the original training trajectories during motion. The CL algorithm is implemented on the transformed unconstrained system while enhancing the learning capability of the proposed algorithm for the exoskeleton. The optimal control with prescribed constraints is analyzed for stability using the Lyapunov theorem. Finally, simulation results validate the effectiveness of the proposed H‐CLOC strategy for lower limb exoskeletons. [ABSTRACT FROM AUTHOR]

Both single and repeated visual stimuli produce waves of activity in the visual cortex of freshwater turtles. Large-scale, biophysically realistic models of the visual cortex capture the basic features of the waves produced by single stimuli. However, these models do not respond to repetitive stimuli due to the presence of a long-lasting hyperpolarization that follows the initial wave. This paper modifies the large-scale model so that it responds to repetitive stimuli by incorporating Hebbian and anti-Hebbian learning rules in synapses in the model. The resulting adaptive model responds to repetitive stimuli with repetitive waves. However, repeated presentation of a stimulus to a restricted region of visual space produces a habituation in the model in the same way it does in the real cortex. Index Terms--Hebbian learning, large-scale cortex model, synaptic adaptation, turtle visual cortex.

In this paper, we study the human oculomotor system as a simple mechanical control system. It is a well known physiological fact that all eye movements obey Listing's law, which states that eye orientations form a subset consisting of rotation matrices for which the axes are orthogonal to the normal gaze direction. First, we discuss the geometry of this restricted configuration space (referred to as the Listing space). Then we formulate the system as a simple mechanical control system with a holonomic constraint. We propose a realistic model with musculotendon complexes and address the question of controlling the gaze. As an example, an optimal energy control problem is formulated and numerically solved. Index Terms--Eye movements, geodesics, Hill model, Listing's law, simple mechanical control systems.

Visual stimuli evoke wave activity in the visual cortex of freshwater turtles. Earlier work from our laboratory showed that information about the positions of stationary visual stimuli is encoded in the spatiotemporal dynamics of the waves and that the waves can be decoded using Bayesian detection theory. This paper extends these results in three ways. First, it shows that flashes of light separated in space and time and stimuli moving with three speeds can be discriminated statistically using the waves generated in a large-scale model of the cortex. Second, it compares the coding capabilities of spike rate and spike time codes. Spike rate codes were obtained by low-pass filtering the activities of individual neurons in the model with filters of different band widths. For the moving targets used in the study, detectability using spike rate codes is immune to the choice of a specific bandwidth, indicating that a coarse filter is able to adequately discriminate targets. Spike timing codes are binary sequences indicating the precise timing of spike activity of individual neurons across the cortex. Spike time codes generally perform better than do spike rate codes. Third, the encoding process is examined in terms of the underlying cellular mechanisms that result in the initiation, propagation and cessation of the wave. The period of peak detectability corresponds to the period in which waves are propagating across the cortex. Index Terms--[beta]-space representation, Karhunen-Loeve (KL) decomposition, motion encoding, Statistical hypothesis testing, turtle visual cortex.

Visual stimuli elicit waves of activity that propagate across the visual cortex of turtles. An earlier study showed that these waves encode information about the positions of stimuli in visual space. This paper addresses the question of how this information can be decoded from the waves. Windowing techniques were used to temporally localize information contained in the wave. Sliding encoding windows were used to represent waves of activity as low dimensional temporal strands in an appropriate space. Expanding detection window (EDW) or sliding detection window (SDW) techniques were combined with statistical hypothesis testing to discriminate input stimuli. Detection based on an EDW was more reliable than detection based on a SDW. Detection performance improved at a very early stage of the cortical response as the length of the detection window is increased. The property of intrinsic noise was explicitly considered. Assuming that the noise is colored provided a more reliable estimate than did the assumption of a white noise in the cortical output. Index Terms--B space representation, Karhunen-Loeve (KL) decomposition, statistical hypothesis testing, turtle visual cortex.

In this paper, an observer problem from a computer vision application is studied. Rigid body pose estimation using inertial sensors and a monocular camera is considered and it is shown how rotation estimation can be decoupled from position estimation. Orientation estimation is formulated as an observer problem with implicit output where the states evolve on SO(3). A careful observability study reveals interesting group theoretic structures tied to the underlying system structure. A locally convergent observer where the states evolve on SO(3) is proposed and numerical estimates of the domain of attraction is given. Further, it is shown that, given convergent orientation estimates, position estimation can be formulated as a linear implicit output problem. From an applications perspective, it is outlined how delayed low bandwidth visual observations and high bandwidth rate gyro measurements can provide high bandwidth estimates. This is consistent with real-time constraints due to the complementary characteristics of the sensors which are fused in a multirate way. Index Terms--Dynamic vision, implicit output, inertial sensors, lie group, observers.

The goal of this paper is to verify that position and velocity of a spot of light incident on the retina of a turtle are encoded by the spatiotemporal dynamics of the cortical waves they generate. This conjecture is examined using a biophysically realistic large-scale computational model of the visual cortex implemented with the software package, GENESIS. The cortical waves are recorded and analyzed using principal components analysis and the position and velocity information from visual space is mapped onto an abstract B-space, to be described, using the coefficients of the principal components expansion. The likely values of the position/velocity are estimated using standard statistical detection methods. Index Terms--Cortical wave, detection, principal components, visual cortex.

In this note, we consider the problem of motion and shape estimation using a camera and a laser range finder. The object considered is a plane which is undergoing a Riccati motion. The camera observes features on the moving plane perspectively. The range finder camera is capable of obtaining the range of the plane along a given "laser plane," which can either be kept fixed or can be altered in time. Finally, we assume that the identification is carried out as soon as the visual and range data is available or alter a suitable temporal integration. In each of these various cases, we derive-to what extent motion and shape parameters are identifiable and characterize the results as orbit of a suitable group. The note does not emphasize any specific choice of algorithms. Index Terms--Affine motion, laser range finder, machine vision, parameter identification, perspective dynamical system, Riccati motion, rigid motion.

In this paper, we study controlled homogeneous dynamical systems and derive conditions under which the system is perspective controllable. We also derive conditions under which the system is observable in the presence of a control over the complex base field. In the absence of any control input, we derive a necessary and sufficient condition for observability of a homogeneous dynamical system over the real base field. The observability criterion obtained generalizes a well known Popov-Belevitch-Hautus (PBH) rank criterion to check the observability of a linear dynamical system. Finally, we introduce rational, exponential, interpolation problems as an important step toward solving the problem of realizing homogeneous dynamical systems with minimum state dimensions. Index Terms--Author, please supply your own keywords or send a blank e-mail to keywords@ieee.org to receive a list of suggested keywords.

In this paper we introduce and study a linear dynamical system with a perspective observation function. The study of these systems has been shown to be useful in motion and shape estimation problems in machine vision. We introduce the notion of perspective observability and obtain under a special case a necessary and sufficient condition that would guarantee observability of the initial condition of the linear dynamical system up to a one-parameter magnitude scaling. Subsequently, a new realization theory is introduced which is useful for studying linear systems with perspective observation. Our main result is to show that parameters can be recovered up to orbits of a suitable "perspective group." A new rescaling algorithm is described to identify parameters up to orbits of the perspective system. The identification problem is further analyzed in detail for various problems that are of interest in machine vision.

In this paper, an earlier result on the problem of observability of a linear dynamical system due to Popov-Belevitch-Hautus has been generalized and applied to the problem of observing the initial condition of a linear dynamical system described on the space of d dimensional affine planes in [R.sup.n.]