Tactile Transfer Learning and Object Recognition With a Multifingered Hand Using Morphology Specific Convolutional Neural Networks.

Multifingered robot hands can be extremely effective in physically exploring and recognizing objects, especially if they are extensively covered with distributed tactile sensors. Convolutional neural networks (CNNs) have been proven successful in processing high dimensional data, such as camera images, and are, therefore, very well suited to analyze distributed tactile information as well. However, a major challenge is to organize tactile inputs coming from different locations on the hand in a coherent structure that could leverage the computational properties of the CNN. Therefore, we introduce a morphology-specific CNN (MS-CNN), in which hierarchical convolutional layers are formed following the physical configuration of the tactile sensors on the robot. We equipped a four-fingered Allegro robot hand with several uSkin tactile sensors; overall, the hand is covered with 240 sensitive elements, each one measuring three-axis contact force. The MS-CNN layers process the tactile data hierarchically: at the level of small local clusters first, then each finger, and then the entire hand. We show experimentally that, after training, the robot hand can successfully recognize objects by a single touch, with a recognition rate of over 95%. Interestingly, the learned MS-CNN representation transfers well to novel tasks: by adding a limited amount of data about new objects, the network can recognize nine types of physical properties

Grasping and Control Issues in Adaptive End Effectors

Research into robotic grasping and manipulation has led to the development of a large number of tendon based end effectors. Many are, however, developed as a research tool, which are limited in application to the laboratory environment. The main reason being that the designs requiring a large number of actuators to be controlled. Due to the space and safety requirements, very few have been developed and commissioned for industrial applications. This paper presents design of a rigid link finger operated by a minimum number of actuators, which may be suitable for a number of adaptive end effectors. The adaptive nature built into the end effector (due to limited number of actuators) presents considerable problems in grasping and control. The paper discusses the issues associated with such designs. The research can be applicable to any adaptive end effectors that are controlled by limited number of actuators and evaluates their suitability in industrial environments

HEAP: A Sensory Driven Distributed Manipulation System

We address the problems of locating, grasping, and removing one or more unknown objects from a given area. In order to accomplish the task we use HEAP, a system of coordinating the motions of the hand and arm. HEAP also includes a laser range finer, mounted at the end of a PUMA 560, allowing the system to obtain multiple views of the workspace. We obtain volumetric information of the objects we locate by fitting superquadric surfaces on the raw range data. The volumetric information is used to ascertain the best hand configuration to enclose and constrain the object stably. The Penn Hand used to grasp the object, is fitted with 14 tactile sensors to determine the contact area and the normal components of the grasping forces. In addition the hand is used as a sensor to avoid any undesired collisions. The objective in grasping the objects is not to impart arbitrary forces on the object, but instead to be able to grasp a variety of objects using a simple grasping scheme assisted with a volumetric description and force and touch sensing

Design of a Multimodal Fingertip Sensor for Dynamic Manipulation

We introduce a spherical fingertip sensor for dynamic manipulation. It is based on barometric pressure and time-of-flight proximity sensors and is low-latency, compact, and physically robust. The sensor uses a trained neural network to estimate the contact location and three-axis contact forces based on data from the pressure sensors, which are embedded within the sensor's sphere of polyurethane rubber. The time-of-flight sensors face in three different outward directions, and an integrated microcontroller samples each of the individual sensors at up to 200 Hz. To quantify the effect of system latency on dynamic manipulation performance, we develop and analyze a metric called the collision impulse ratio and characterize the end-to-end latency of our new sensor. We also present experimental demonstrations with the sensor, including measuring contact transitions, performing coarse mapping, maintaining a contact force with a moving object, and reacting to avoid collisions.Comment: 6 pages, 2 pages of references, supplementary video at https://youtu.be/HGSdcW_aans. Submitted to ICRA 202

Sensors for Robotic Hands: A Survey of State of the Art

Recent decades have seen significant progress in the field of artificial hands. Most of the surveys, which try to capture the latest developments in this field, focused on actuation and control systems of these devices. In this paper, our goal is to provide a comprehensive survey of the sensors for artificial hands. In order to present the evolution of the field, we cover five year periods starting at the turn of the millennium. At each period, we present the robot hands with a focus on their sensor systems dividing them into categories, such as prosthetics, research devices, and industrial end-effectors.We also cover the sensors developed for robot hand usage in each era. Finally, the period between 2010 and 2015 introduces the reader to the state of the art and also hints to the future directions in the sensor development for artificial hands

Performance of modified jatropha oil in combination with hexagonal boron nitride particles as a bio-based lubricant for green machining

This study evaluates the machining performance of newly developed modified jatropha oils (MJO1, MJO3 and MJO5), both with and without hexagonal boron nitride (hBN) particles (ranging between 0.05 and 0.5 wt%) during turning of AISI 1045 using minimum quantity lubrication (MQL). The experimental results indicated that, viscosity improved with the increase in MJOs molar ratio and hBN concentration. Excellent tribological behaviours is found to correlated with a better machining performance were achieved by MJO5a with 0.05 wt%. The MJO5a sample showed the lowest values of cutting force, cutting temperature and surface roughness, with a prolonged tool life and less tool wear, qualifying itself to be a potential alternative to the synthetic ester, with regard to the environmental concern

Ground Robotic Hand Applications for the Space Program study (GRASP)

This document reports on a NASA-STDP effort to address research interests of the NASA Kennedy Space Center (KSC) through a study entitled, Ground Robotic-Hand Applications for the Space Program (GRASP). The primary objective of the GRASP study was to identify beneficial applications of specialized end-effectors and robotic hand devices for automating any ground operations which are performed at the Kennedy Space Center. Thus, operations for expendable vehicles, the Space Shuttle and its components, and all payloads were included in the study. Typical benefits of automating operations, or augmenting human operators performing physical tasks, include: reduced costs; enhanced safety and reliability; and reduced processing turnaround time

Graphite immobilisation in glass composite materials

Irradiated graphite is a problematic nuclear waste stream and currently raises significant concern worldwide in identifying its long-term disposal route. This thesis describes the use of glass materials for the immobilisation of irradiated graphite prepared by microwave, conventional and sparks plasma sintering methods. Several potential glass compositions namely iron phosphate, aluminoborosilicate, calcium aluminosilicate, alkali borosilicate and obsidian were considered for the immobilisation of various loadings of graphite simulating irradiated graphite. The properties of the samples produced using different processing methods are compared selectively. An investigation of microwave processing using an iron phosphate glass composition revealed that full reaction of the raw materials and formation of a glass melt occurs with consequent removal of porosity at 8 minutes microwave processing. When graphite is present, iron phosphate crystalline phases are formed with much higher levels of residual porosity of up to 43 % than in the samples prepared using conventional sintering under argon. It is found that graphite reacts with the microwave field when in powder form but this reaction is minimised when the graphite is incorporated into a pellet, and that the graphite also impedes sintering of the glass. Mössbauer spectroscopy indicates that reduction of iron occurs with concomitant graphite oxidation. The production of graphite-glass samples using various powdered glass compositions by conventional sintering method still resulted in high porosity with an average of 6-17 % for graphite loadings of 20-25 wt%. Due to the use of pre-made glasses and controlled sintering parameters, the loss of graphite from the total mass is reduced compared to the microwaved samples; the average mass loss is < 0.8 %. The complication of iron oxidation and reduction is present in all the iron containing base glasses considered and this increases the total porosity of the graphite-glass samples. It is concluded that the presence of iron in the raw materials or base glasses as an encapsulation media for the immobilisation of the irradiated graphite waste is not advisable. The production of glass and graphite-glass samples based calcium aluminosilicate composition by spark plasma sintering method is found highly suitable for the immobilisation of irradiated graphite wastes. The advantages of the method includes short processing time i.e. < 40 minutes, improved sintering transport mechanisms, limited graphite oxidation, low porosity (1-4 %) and acceptable tensile strength (2-7 MPa). The most promising samples prepared using spark plasma sintering method were loaded with 30-50 wt% graphite

Doctor of Philosophy

dissertationTactile sensors are a group of sensors that are widely being developed for transduction of touch, force and pressure in the field of robotics, contact sensing and gait analysis. These sensors are employed to measure and register interactions between contact surfaces and the surrounding environment. Since these sensors have gained usage in the field of robotics and gait analysis, there is a need for these sensors to be ultra flexible, highly reliable and capable of measuring pressure and two-axial shear simultaneously. The sensors that are currently available are not capable of achieving all the aforementioned qualities. The goal of this work is to design and develop such a flexible tactile sensor array based on a capacitive sensing scheme and we call it the flexible tactile imager (FTI). The developed design can be easily multiplexed into a high-density array of 676 multi-fingered capacitors that are capable of measuring pressure and two-axial shear simultaneously while maintaining sensor flexibility and reliability. The sensitivity of normal and shear stress for the FTI are 0.74/MPa and 79.5/GPa, respectively, and the resolvable displacement and velocity are as low as 60 µm and 100 µm/s, respectively. The developed FTI demonstrates the ability to detect pressure and shear contours of objects rolling on top of it and capability to measure microdisplacement and microvelocities that are desirable during gait analysis