Integrated Circuitry to Detect Slippage Inspired by Human Skin and Artificial Retinas

This paper presents a bioinspired integrated tactile coprocessor that is able to generate a warning in the case of slippage via the data provided by a tactile sensor. Some implementations use different layers of piezoresistive and piezoelectric materials to build upon the raw sensor and obtain the static (pressure) as well as the dynamic (slippage) information. In this paper, a simple raw sensor is used, and a circuitry is implemented, which is able to extract the dynamic information from a single piezoresistive layer. The circuitry was inspired by structures found in human skin and retina, as they are biological systems made up of a dense network of receptors. It is largely based on an artificial retina , which is able to detect motion by using relatively simple spatial temporal dynamics. The circuitry was adapted to respond in the bandwidth of microvibrations produced by early slippage, resembling human skin. Experimental measurements from a chip implemented in a 0.35-mum four-metal two-poly standard CMOS process are presented to show both the performance of the building blocks included in each processing node and the operation of the whole system as a detector of early slippage.Ministerio de Economía y Competitividad TEC2006-12376-C02-01Gobierno de España TEC2006- 1572

Three Realizations and Comparison of Hardware for Piezoresistive Tactile Sensors

Tactile sensors are basically arrays of force sensors that are intended to emulate the skin in applications such as assistive robotics. Local electronics are usually implemented to reduce errors and interference caused by long wires. Realizations based on standard microcontrollers, Programmable Systems on Chip (PSoCs) and Field Programmable Gate Arrays (FPGAs) have been proposed by the authors for the case of piezoresistive tactile sensors. The solution employing FPGAs is especially relevant since their performance is closer to that of Application Specific Integrated Circuits (ASICs) than that of the other devices. This paper presents an implementation of such an idea for a specific sensor. For the purpose of comparison, the circuitry based on the other devices is also made for the same sensor. This paper discusses the implementation issues, provides details regarding the design of the hardware based on the three devices and compares them.This work has been partially funded by the Spanish Government under contracts TEC2006-12376 and TEC2009-14446

A Neural Model of Timed Response Learning in the Cerebellum

A spectral timing model is developed to explain how the cerebellum learns adaptively timed responses during the rabbit's conditioned nictitating membrane response (NMR). The model posits two learning sites that respectively enable conditioned excitation and timed disinhibition of the response. Long-term potentiation of mossy fiber pathways projecting to interpositus nucleus cells allows conditioned excitation of the response's adaptive gain. Long-term depression of parallel fiber- Purkinje cell synapses in the cerebellar cortex allows learning of an adaptively timed reduction in Purkinje cell inhibition of the same nuclear cells. A spectrum of partially timed responses summate to generate an accurately timed population response. In agreement with physiological data, the model Purkinje cell activity decreases in the interval following the onset of the conditioned stimulus, and nuclear cell responses match conditioned response (CR) topography. The model reproduces key behavioral features of the NMR, including the properties that CR peak amplitude occurs at the unconditioned stimulus (US) onset, a discrete CR peak shift occurs with a change in interstimulus interval (ISI) between conditioned stim- ulus (CS) and US, mixed training at two different ISis produces a double-peaked CR, CR acquisition and rate of responding depend unimodally on the lSI, CR onset latency decreases during training, and maladaptively-timed, small-amplitude CRs result from ablation of cerebellar cortex.National Science Foundation (IRI-90-24877); Office of Naval Research (N00014-92-J-1309); Air Force Office of Scientific Research (F49620-92-J-0225

Study to design and develop remote manipulator system

Modeling of human performance in remote manipulation tasks is reported by automated procedures using computers to analyze and count motions during a manipulation task. Performance is monitored by an on-line computer capable of measuring the joint angles of both master and slave and in some cases the trajectory and velocity of the hand itself. In this way the operator's strategies with different transmission delays, displays, tasks, and manipulators can be analyzed in detail for comparison. Some progress is described in obtaining a set of standard tasks and difficulty measures for evaluating manipulator performance