A novel event-based incipient slip detection using Dynamic Active-Pixel Vision Sensor (DAVIS)

In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to detect incipient slip, slip, stress distribution and object vibration. Thirty-seven experiments were performed on five objects with different sizes, shapes, materials and weights to compare precision and response time of the proposed approach. The proposed approach is validated by using a high speed constitutional camera (1000 FPS). The results indicate that the sensor can detect incipient slippage with an average of 44.1 ms latency in unstructured environment for various objects. It is worth mentioning that the experiments were conducted in an uncontrolled experimental environment, therefore adding high noise levels that affected results significantly. However, eleven of the experiments had a detection latency below 10 ms which shows the capability of this method. The results are very promising and show a high potential of the sensor being used for manipulation applications especially in dynamic environments

Neuromorphic event-based slip detection and suppression in robotic grasping and manipulation

Slip detection is essential for robots to make robust grasping and fine manipulation. In this paper, a novel dynamic vision-based finger system for slip detection and suppression is proposed. We also present a baseline and feature based approach to detect object slips under illumination and vibration uncertainty. A threshold method is devised to autonomously sample noise in real-time to improve slip detection. Moreover, a fuzzy based suppression strategy using incipient slip feedback is proposed for regulating the grip force. A comprehensive experimental study of our proposed approaches under uncertainty and system for high-performance precision manipulation are presented. We also propose a slip metric to evaluate such performance quantitatively. Results indicate that the system can effectively detect incipient slip events at a sampling rate of 2kHz ($\Delta t = 500\mu s$) and suppress them before a gross slip occurs. The event-based approach holds promises to high precision manipulation task requirement in industrial manufacturing and household services.Comment: 18 pages, 14 figure

Exploring Long-term Fault Evolution in Obliquely Loaded Systems Using Tabletop Experiments and Digital Image Correlation Techniques

This thesis focuses on the use of scaled physical experiments to better understand the development and long-term evolution of fault systems that are otherwise impossible to observe directly. The document is divided into three chapters. The first chapter documents the implementation of an inexpensive stereo vision method for acquiring high resolution three-dimensional strain data for table-top experiments. The second chapter applies the stereo vision method to a tectonic problem—the development of slip partitioning in obliquely loaded crustal systems. Slip partitioned fault systems accommodate oblique convergence with different slip rake on two or more faults and are well documented in the crust. In this chapter, we simulate oblique convergence using blocks with 30° dipping contacts under wet kaolin clay. The experiments reveal three styles of slip partitioning development—contingent upon convergence angle and the presence or absence of a pre-existing vertical fault. Across all experiments, the slip rates along slip-partitioned faults vary temporally suggesting that the faults continuously adjust to conditions produced by the other fault. The lack of steady state in the experiments suggests that slip-partitioned crustal systems may also evolve with oscillating behavior rather than developing a single efficient active fault structure to accommodate oblique convergence. The third chapter documents rheological tests of wet kaolin for applications to crustal deformation experiments. This chapter investigates thixotropy in the clay as well as the role of grain size distribution and water content on its shear strength

Haptics: Science, Technology, Applications

This open access book constitutes the proceedings of the 13th International Conference on Human Haptic Sensing and Touch Enabled Computer Applications, EuroHaptics 2022, held in Hamburg, Germany, in May 2022. The 36 regular papers included in this book were carefully reviewed and selected from 129 submissions. They were organized in topical sections as follows: haptic science; haptic technology; and haptic applications

Neuromorphic vision-based tactile sensor for robotic grasp

Tactile sensors are developed to mimic human sense of touch in robotics. The touch sense is essential for machines to interact with environment. Several approaches have been studied to obtain rich information from the contact point to correct robot’s actions and acquire further information about the objects. Vision-based tactile sensors aim to extract tactile information by observing the contact point between the robot’s hand and environment and applying computer vision algorithms. In this thesis, a novel class of vision-based tactile sensors is proposed, "Neuromorphic Vision-Based Tactile Sensor" to estimate the contact force and classify materials in a grasp. This novel approach utilises a neuromorphic vision sensor to capture intensity changes (events) in the contact point. The triggered events represent changes in the contact force at each pixel in microseconds. The proposed sensor has a high temporal resolution and dynamic range which are suitable for high-speed robotic applications. Initially, a general framework is demonstrated to show the sensor operations. Furthermore, the relationship between events and the contact force is presented. Afterwards, methods based on Time-Delay Neural Networks (TDNN), Gaussian Process (GP) and Deep Neural Networks (DNN) are developed to estimate the contact force and classify objects material from the accumulation of events. The results indicate a low mean squared error of 0.17N against a force sensor for the force estimation using TDNN. Moreover, the objects materials are classified with 79.12% accuracy which is 30% higher compared to piezoresistive force sensors. This is followed by an approach to preserve spatio-temporal information during the learning process. Therefore, the triggered events are framed (event-frames) within a time window to preserve spatial information. Afterwards, multiple types of Long Short-Term Memory (LSTM) networks with convolutional layers are developed to estimate the contact force for objects with different size. The results are validated against a force sensor and achieve a mean squared error of less than 0.1N. Finally, algorithmic augmentation techniques are investigated to improve the networks accuracy for a wider range of force. Image-based and time-series augmentation methods are developed to generate artificial samples for training the network. A novel time-domain approach Temporal Event Shifting (TES) is proposed to augment events by preserving the spatial information of events. The results are validated on real experiments which indicate that time-domain and hybrid augmentation methods improve the networks’ accuracy significantly considering an object with a different size

NASA Tech Briefs, November 2009

Topics covered include: Cryogenic Chamber for Servo-Hydraulic Materials Testing; Apparatus Measures Thermal Conductance Through a Thin Sample from Cryogenic to Room Temperature; Rover Attitude and Pointing System Simulation Testbed; Desktop Application Program to Simulate Cargo-Air-Drop Tests; Multimodal Friction Ignition Tester; Small-Bolt Torque-Tension Tester; Integrated Spacesuit Audio System Enhances Speech Quality and Reduces Noise; Hardware Implementation of a Bilateral Subtraction Filter; Simple Optoelectronic Feedback in Microwave Oscillators; Small X-Band Oscillator Antennas; Free-Space Optical Interconnect Employing VCSEL Diodes; Discrete Fourier Transform Analysis in a Complex Vector Space; Miniature Scroll Pumps Fabricated by LIGA; Self-Assembling, Flexible, Pre-Ceramic Composite Preforms; Flight-speed Integral Image Analysis Toolkit; Work Coordination Engine; Multi-Mission Automated Task Invocation Subsystem; Autonomously Calibrating a Quadrupole Mass Spectrometer; Determining Spacecraft Reaction Wheel Friction Parameters; Composite Silica Aerogels Opacified with Titania; Multiplexed Colorimetric Solid-Phase Extraction; Detecting Airborne Mercury by Use of Polymer/Carbon Films; Lattice-Matched Semiconductor Layers on Single Crystalline Sapphire Substrate; Pressure-Energized Seal Rings to Better Withstand Flows; Rollerjaw Rock Crusher; Microwave Sterilization and Depyrogenation System; Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images; NiF2/NaF:CaF2/Ca Solid-State High-Temperature Battery Cells; Critical Coupling Between Optical Fibers and WGM Resonators; Microwave Temperature Profiler Mounted in a Standard Airborne Research Canister; Alternative Determination of Density of the Titan Atmosphere; Solar Rejection Filter for Large Telescopes; Automated CFD for Generation of Airfoil Performance Tables; Progressive Classification Using Support Vector Machines; Active Learning with Irrelevant Examples; A Data Matrix Method for Improving the Quantification of Element Percentages of SEM/EDX Analysis; Deployable Shroud for the International X-Ray Observatory; Improved Model of a Mercury Ring Damper; Optoelectronic pH Meter: Further Details; X-38 Advanced Sublimator; and Solar Simulator Represents the Mars Surface Solar Environment