NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

NASA space station automation: AI-based technology review. Executive summary

Research and Development projects in automation technology for the Space Station are described. Artificial Intelligence (AI) based technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics

Optical Force/Tactile Sensors for Robotic Applications

Nowadays, robotic systems use tactile sensing as a key enabling technology to implement complex tasks. For example, manipulation and grasping problems strongly depend on the physical and geometrical characteristics of the objects; in fact, objects may be deformable or change their shape when in contact with the robot or the environment. For this reason, often, robots end effectors are equipped with sensorized fingers which can estimate the objects' features, forces, and contact locations. This is useful in a safe and efficient physical Human-Robot Interaction (pHRI) to perform cooperation and co-manipulation tasks while limiting damage from accidental impacts

Objekt-Manipulation und Steuerung der Greifkraft durch Verwendung von Taktilen Sensoren

This dissertation describes a new type of tactile sensor and an improved version of the dynamic tactile sensing approach that can provide a regularly updated and accurate estimate of minimum applied forces for use in the control of gripper manipulation. The pre-slip sensing algorithm is proposed and implemented into two-finger robot gripper. An algorithm that can discriminate between types of contact surface and recognize objects at the contact stage is also proposed. A technique for recognizing objects using tactile sensor arrays, and a method based on the quadric surface parameter for classifying grasped objects is described. Tactile arrays can recognize surface types on contact, making it possible for a tactile system to recognize translation, rotation, and scaling of an object independently.Diese Dissertation beschreibt eine neue Art von taktilen Sensoren und einen verbesserten Ansatz zur dynamischen Erfassung von taktilen daten, der in regelmäßigen Zeitabständen eine genaue Bewertung der minimalen Greifkraft liefert, die zur Steuerung des Greifers nötig ist. Ein Berechnungsverfahren zur Voraussage des Schlupfs, das in einen Zwei-Finger-Greifarm eines Roboters eingebaut wurde, wird vorgestellt. Auch ein Algorithmus zur Unterscheidung von verschiedenen Oberflächenarten und zur Erkennung von Objektformen bei der Berührung wird vorgestellt. Ein Verfahren zur Objekterkennung mit Hilfe einer Matrix aus taktilen Sensoren und eine Methode zur Klassifikation ergriffener Objekte, basierend auf den Daten einer rechteckigen Oberfläche, werden beschrieben. Mit Hilfe dieser Matrix können unter schiedliche Arten von Oberflächen bei Berührung erkannt werden, was es für das Tastsystem möglich macht, Verschiebung, Drehung und Größe eines Objektes unabhängig voneinander zu erkennen

Object Recognition and Localization : the Role of Tactile Sensors

Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This thesis presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Sequential Filter (BRICPSF) is based on an innovative combination of a sequential filter, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC) algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in simulation and using actual hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses BRICPSF for object part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments

Development of PVDF tactile dynamic sensing in a behaviour-based assembly robot

The research presented in this thesis focuses on the development of tactile event sig¬ nature sensors and their application, especially in reactive behaviour-based robotic assembly systems.In pursuit of practical and economic sensors for detecting part contact, the application ofPVDF (polyvinylidene fluoride) film, a mechanical vibration sensitive piezo material, is investigated. A Clunk Sensor is developed which remotely detects impact vibrations, and a Push Sensor is developed which senses small changes in the deformation of a compliant finger surface. The Push Sensor is further developed to provide some force direction and force pattern sensing capability.By being able to detect changes of state in an assembly, such as a change of contact force, an assembly robot can be well informed of current conditions. The complex structure of assembly tasks provides a rich context within which to interpret changes of state, so simple binary sensors can conveniently supply a lot more information than in the domain of mobile robots. Guarded motions, for example, which require sensing a change of state, have long been recognised as very useful in part mating tasks. Guarded motions are particularly well suited to be components of assembly behavioural modules.In behaviour-based robotic assembly systems, the high level planner is endowed with as little complexity as possible while the low level planning execution agent deals with actual sensing and action. Highly reactive execution agents can provide advantages by encapsulating low level sensing and action, hiding the details of sensori-motor complexity from the higher levels.Because behaviour-based assembly systems emphasise the utility of this kind of quali¬ tative state-change sensor (as opposed to sensors which measure physical quantities), the robustness and utility of the Push Sensor was tested in an experimental behaviourbased system. An experimental task of pushing a ring along a convoluted stiff wire is chosen, in which the tactile sensors developed here are aided by vision. Three differ¬ ent methods of combining these different sensors within the general behaviour-based paradigm are implemented and compared. This exercise confirms the robustness and utility of the PVDF-based tactile sensors. We argue that the comparison suggests that for behaviour-based assembly systems using multiple concurrent sensor systems, bottom-level motor control in terms of force or velocity would be more appropriate than positional control. Behaviour-based systems have traditionally tried to avoid symbolic knowledge. Considering this in the light of the above work, it was found useful to develop a taxonomy of type of knowledge and refine the prohibition

Design and Development of Sensor Integrated Robotic Hand

Most of the automated systems using robots as agents do use few sensors according to the need. However, there are situations where the tasks carried out by the end-effector, or for that matter by the robot hand needs multiple sensors. The hand, to make the best use of these sensors, and behave autonomously, requires a set of appropriate types of sensors which could be integrated in proper manners. The present research work aims at developing a sensor integrated robot hand that can collect information related to the assigned tasks, assimilate there correctly and then do task action as appropriate. The process of development involves selection of sensors of right types and of right specification, locating then at proper places in the hand, checking their functionality individually and calibrating them for the envisaged process. Since the sensors need to be integrated so that they perform in the desired manner collectively, an integration platform is created using NI PXIe-1082. A set of algorithm is developed for achieving the integrated model. The entire process is first modelled and simulated off line for possible modification in order to ensure that all the sensors do contribute towards the autonomy of the hand for desired activity. This work also involves design of a two-fingered gripper. The design is made in such a way that it is capable of carrying out the desired tasks and can accommodate all the sensors within its fold. The developed sensor integrated hand has been put to work and its performance test has been carried out. This hand can be very useful for part assembly work in industries for any shape of part with a limit on the size of the part in mind. The broad aim is to design, model simulate and develop an advanced robotic hand. Sensors for pick up contacts pressure, force, torque, position, surface profile shape using suitable sensing elements in a robot hand are to be introduced. The hand is a complex structure with large number of degrees of freedom and has multiple sensing capabilities apart from the associated sensing assistance from other organs. The present work is envisaged to add multiple sensors to a two-fingered robotic hand having motion capabilities and constraints similar to the human hand. There has been a good amount of research and development in this field during the last two decades a lot remains to be explored and achieved. The objective of the proposed work is to design, simulate and develop a sensor integrated robotic hand. Its potential applications can be proposed for industrial environments and in healthcare field. The industrial applications include electronic assembly tasks, lighter inspection tasks, etc. Application in healthcare could be in the areas of rehabilitation and assistive techniques. The work also aims to establish the requirement of the robotic hand for the target application areas, to identify the suitable kinds and model of sensors that can be integrated on hand control system. Functioning of motors in the robotic hand and integration of appropriate sensors for the desired motion is explained for the control of the various elements of the hand. Additional sensors, capable of collecting external information and information about the object for manipulation is explored. Processes are designed using various software and hardware tools such as mathematical computation MATLAB, OpenCV library and LabVIEW 2013 DAQ system as applicable, validated theoretically and finally implemented to develop an intelligent robotic hand. The multiple smart sensors are installed on a standard six degree-of-freedom industrial robot KAWASAKI RS06L articulated manipulator, with the two-finger pneumatic SHUNK robotic hand or designed prototype and robot control programs are integrated in such a manner that allows easy application of grasping in an industrial pick-and-place operation where the characteristics of the object can vary or are unknown. The effectiveness of the actual recommended structure is usually proven simply by experiments using calibration involving sensors and manipulator. The dissertation concludes with a summary of the contribution and the scope of further work

Computer hardware and software for robotic control

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems

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