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

The Design And Validations Of The Ultrasonic Tactile Sensor

An ultrasonic tactile sensor that can measure the stiffness of the tissue was developed. By combining analytical and numerical approaches, efficient design methodology was presented. The electrical and mechanical performance of developed sensor was experimentally validated

Safe Local Navigation for Visually Impaired Users With a Time-of-Flight and Haptic Feedback Device

This paper presents ALVU (Array of Lidars and Vibrotactile Units), a contactless, intuitive, hands-free, and discreet wearable device that allows visually impaired users to detect low- and high-hanging obstacles, as well as physical boundaries in their immediate environment. The solution allows for safe local navigation in both confined and open spaces by enabling the user to distinguish free space from obstacles. The device presented is composed of two parts: a sensor belt and a haptic strap. The sensor belt is an array of time-of-flight distance sensors worn around the front of a user's waist, and the pulses of infrared light provide reliable and accurate measurements of the distances between the user and surrounding obstacles or surfaces. The haptic strap communicates the measured distances through an array of vibratory motors worn around the user's upper abdomen, providing haptic feedback. The linear vibration motors are combined with a point-loaded pretensioned applicator to transmit isolated vibrations to the user. We validated the device's capability in an extensive user study entailing 162 trials with 12 blind users. Users wearing the device successfully walked through hallways, avoided obstacles, and detected staircases.Andrea Bocelli FoundationNational Science Foundation (U.S.) (Grant NSF IIS1226883

Method to determine physical properties of the ground

The method can determine physical properties of the ground stepped upon by a user wearing a footwear incorporating an accelerometer, and includes: receiving a raw signal from the accelerometer during at least one step being taken by the user on the ground; identifying, in the received raw signal, at least one characteristic signature; associating the at least one characteristic signature to physical properties of the ground; and generating a signal indicating the physical properties based on said association. The generated signal can further be used to advise a user of a risk of falling based on at least the physical properties of the ground

Position sensing in restricted environments in automated manufacturing

This thesis describes a successful attempt to identify angular movement of leather components, when transported from one operation to another, by a conveyor system. The automated manufacturing process of skiving leather components was utilised for this research. Skiving is the localised thinning of the leather components to enable the joining of these without forming thick and unsightly joints. This process had been automated, but its performance could be enhanced by combining an additional sensing system. The research work was directed towards integrating a relatively small and low-cost form of sensing system onto a dynamic matrix skiving machine. Two key areas of the research were the identification of suitable sensor technology and the investigation of the environment within which they operate. The sensors form a vital and necessary part of any type of identification process and are used to acquire relevant data. The thesis describes a variety of sensor technologies and their suitability for use in restrictive environments. These environmental restrictions of the skiving process and the component material influence the choice of sensor. Following the study of sensor technologies, the second phase was aimed at implementing an automatic position sensing system. Therefore the main specification of the system was to detect the leather components, and their orientation prior to, and following transportation through the process. The final part of this work presents the results obtained from the introduction of the sensing arrays. It also identifies areas that may be investigated further to improve the system, concerning the particular restricted environment utilised in this research

Digital photoelasticity in biomedical sensing.

This research investigates on the use of digital photoelasticityin biomedical sensing applications with a particular emphasis on assessment of diabetic foot ulceration. One of the main causes of foot ulceration in diabetic patients is excessive pressure at the sole of the foot, which involves vertical as well as shear forces. Precise role of these forces in predisposing the foot to ulceration is not very well understood, however, a general consensus is that the combined effect of vertical and shear forces is much more harmful than the vertical force alone. Whilst the vertical force can be measured relatively easily,it is difficult to decouple the shear force from the combined force,which is considered to be of more clinical relevance in assessment of diabetic foot ulceration. The major impediment in achieving this objective is lack of suitable shear force measuring devices and limitation of the existing systems that can simulate the actual conditions of foot loading. In this research a photoelastic material has been used to develop a prototype-sensing device, which develops coloured fringes due to foot loading. Intelligent image processing techniques have been employed to analyse and obtain relevant load information from these fringes. The research surveys the existing sensing devices that are commonly used in diabetic foot clinics. It highlights the need for a new sensor design that can be used for pressure-induced pathologies. To meet these requirements and develop a sensor based on the principle of photoelasticity, conventional techniques of RGB photoelasticity and Phase-shifting methods have been fully investigated. This led to identify suitable optical elements for the system design and applicability of these techniques for the intended application. This resulted in devising an experimental set up that can provide coloured image of foot per se actual conditions of foot loading. However, the conventional technique of stress analysis cannot be directly applied in the present case, since the photoelastic effect is induced due to the material deformation as opposed to the usual component loading in photoelastic experiments with coatings. Also, in the current application the applied load has to be estimated from the fringe patterns (i.e. inverse problem) under varying environmental conditions with different loading situations for each subject. As it is difficult to develop analytical models under these conditions and the related inverse might have infinite number of solutions, the use of neural networks has been proposed to overcome these complexities. The network has been trained with direct image data which provides input load information under controlled experimental conditions of vertical as well as shear forces. The prototype sensor also provides qualitative whole-field data of the actual foot loading, which can be used for quick differentiation of foot with or without callus. This may also find use in haptics, pattern recognition and other biomedical sensing applications such as pressure sore assessment for disabled subjects or patients with numbness. With further enhancement in image processing technique this can be developed into a clinically viable system capable of providing complete foot analysis from early stage detection to prevention of ulceration

Incipient slip detection and grasping automation for robotic surgery

Robotic minimally invasive surgery provides multiple improvements over traditional laparoscopic procedures, but one significant issue still encountered is their limited force control during the grasping and retraction of tissue, as the surgeon is separated from the instrument, and therefore denuded of their sense of touch and the applied forces. Prior solutions have largely looked towards haptic feedback to resolve this issue, but an alternative approach is to detect and monitor the occurrence of tissue slip events. This would allow the force to be automatically adjusted to prevent slip, minimising the clamp force used to maintain control, thus reducing the probability of tissue trauma. The aim of this work is to develop a method for the early detection and mitigation of tissue slip during robotic surgical manipulation tasks, helping to reduce tissue trauma and minimise tissue slip events. Initial investigations into literature, and evaluation of the slip mechanics when grasping soft, lubricated, deformable materials, indicated that small localised slips occur before the onset of macro slip. Two phenomena were identified in the slip mechanics investigation that could be employed to induce these slip in a measurable and repeatable manner. Firstly through using the tissue's deformable properties to create slip differentials between the front and rear of the grasper face, and secondly through using a curved surface to create a variation in the normal force, and thus frictional force, across the surface. Two instrumented grasper faces were developed, based on each of these phenomena, that were capable of monitoring the occurrence of localised tissue slip through monitoring the displacement of a series of independent movable islands that made up the grasper face. These were then demonstrated to be capable of automatically detecting slip events for a range of test conditions with tissue simulants, before being utilised to automatically control the grasping forces during a tissue retraction task. Both sensor systems provided similar levels of tissue control to one which utilised the maximum clamp force throughout the task, whilst applying lower forces during the early stages of retraction, reducing the probability of tissue damage. In addition the normal force based method, with the curved grasper face, was demonstrated to be effective for the early detection of slip when grasping porcine liver tissue, successfully detecting incipient slip in 77% of cases. This work provides a strong basis for further development of incipient slip sensing for surgical applications. It provides novel contributions in the understanding of slip mechanics of soft tissues, as well as presenting two separate novel sensing approaches for the automatic detection and mitigation of slip events, offering an opportunity for reducing the occurrence of tissue slip events whilst minimising tissue trauma, as well as surgeon fatigue