Joel W. Burdick

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This paper combines wavelet transforms with basic detection theory to develop a new unsupervised method for robustly detecting and localizing spikes in noisy neural recordings. The method does not require the construction of templates, or the supervised setting of thresholds. We present extensive Monte Carlo simulations, based on actual extracellular(More)
BACKGROUND Repeated periods of stimulation of the spinal cord and training increased the ability to control movement in animal models of spinal cord injury. We hypothesised that tonic epidural spinal cord stimulation can modulate spinal circuitry in human beings into a physiological state that enables sensory input from standing and stepping movements to(More)
The hierarchical generalized Voronoi graph (HGVG) is a new roadmap developed for sensor-based exploration in unknown environments. This paper defines the HGVG structure: a robot can plan a path between two locations in its work space or configuration space by simply planning a path onto the HGVG, then along the HGVG, and finally from the HGVG to the goal.(More)
AbsfractThis paper presents novel and efficient kinematic modeling techniques for “hyper-redundant” robots. This approach is based on a “backbone curve” that captures the robot’s macroscopic geometric features. The inverse kinematic, or “hyper-redundancy resolution,” problem reduces to determining the time varying backbone curve behavior. To efficiently(More)
This paper presents an algorithm to find the line-based map that best fits sets of two-dimensional range scan data that are acquired from multiple poses. To construct these maps, we first provide an accurate means to fit a line segment to a set of uncertain points via a maximum likelihood formalism. This scheme weights each point’s influence on the fit(More)
The prospect of assisting disabled patients by translating neural activity from the brain into control signals for prosthetic devices, has flourished in recent years. Current systems rely on neural activity present during natural arm movements. We propose here that neural activity present before or even without natural arm movements can provide an(More)
This paper introduces a generalized framework, termed “stochastic cloning,” for processing relative state measurements within a Kalman filter estimator. The main motivation and application for this methodology is the problem of fusing displacement measurements with position estimates for mobile robot localization. Previous approaches have ignored the(More)
This paper presents a decentralized motion planning algorithm for the distributed sensing of a noisy dynamical process by multiple cooperating mobile sensor agents. This problem is motivated by localization and tracking tasks of dynamic targets. Our gradient-descent method is based on a cost function that measures the overall quality of sensing. We also(More)
This paper considers the kinematics of hyperredundant (or “serpentine”) robot locomotion over uneven solid terrain, and presents algorithms to implement a variety of “gaits.” The analysis and algorithms are based on a continuous backbone curve model which captures the robot’s macroscopic geometry. Two classes of gaits, based on stationary waves and(More)