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Initially developed as a close quarters inspection tool capable of accessing hard to reach, tight, or visibly restricted, areas of satellites, the VIPIR system can be used to remotely inspect inaccessible locations such as behind a sheet of thermal blanketing material, into a satellites plumbing, or perhaps even deep inside the otherwise unreachable crevasses of a spacecraft bus. The VIPIR system incorporates a number of subassemblies for incredible operational freedom and capabilities for imaging and dissemination of componentry. VIPIR’s Video Borescope Assembly (VBA) is a flexible snake-camera capable of multidirectional articulations, making steering and control simple and intuitive for an operator. The VBA also includes at least one imaging sensor and lighting to see in dark, confined spaces. Real-time, high-resolution visual information can be fed back to an operator for live analysis. A reel system extends and retracts the VBA with the use of a spool, and includes position indicators for deployment tracking. The Tendon Management System (TMS), not unlike human tendons, utilizes pulleys and tensioners to articulate the VBA in the confined spaces. A seal system ensures the VBA is free of contamination. VIPIR underwent space-based testing on the ISS during the Robotic Refueling Phase 2 (RRM-2) mission designed to showcase and test several NASA advanced robotic satellite servicing technologies. During this mission, VIPIR demonstrated state-of-the-art near and midrange inspection capabilities. NASA’s VIPIR system is available for licensing to industry, and may be desirable to companies focused on satellite servicing, on-orbit assembly, and other applications requiring detailed inspection of assets in space.

The Client Berthing System (CBS) was originally designed for NASA’s On-orbit Servicing, Assembly, and Manufacturing 1 (OSAM-1) spacecraft, which will grapple and refuel the LandSat 7 satellite. After the OSAM-1 spacecraft has rendezvoused with LandSat 7, a robotic arm equipped with a gripper tool will autonomously grapple the satellite’s Marman ring (launch separation ring) and affix it to the CBS in the appropriate refueling position. The CBS is comprised of three posts protruding from the servicing satellite, each with integrated berthing mechanisms, distributed in a radial pattern of 120° along the client’s Marman ring diameter. Each berthing mechanism includes a rotary clamping jaw with a drawdown and radial contact portion. The clamping jaws are actuated by a motor-driven leadscrew and guided by recirculating linear ball bearings. After the servicing spacecraft’s robotic arm has placed the client satellite Marman ring into the CBS berthing box, the clamping jaws simultaneously move radially inward towards the center of the ring. The lead-in features of the jaws exert downward pressure on the ring, driving it towards the jaw palms as the lead-in portion rises over the surface of the ring flange. Once the flange is drawn down such that it contacts the radial clamp surface of the jaws, force is exerted causing the jaws to pivot, driving the underside of the lead-in surfaces into contact with the upper flange surface. As the jaw mechanisms continue to drive, increased axial load squeezes the ring flange between the lead-in-feature and palm of the jaws, stabilizing the connection. At a predetermined load, brakes are engaged, and system motors shut off. A NASA-developed Marman ring location detection system is employed to guide the berthing process. NASA has developed a suite of cutting-edge technologies that can help your business develop robust satellite servicing offerings. For additional information, please see the NASA Satellite Servicing Technologies Available for Licensing link provided.

Originally developed by NASA and GM, the Robo-Glove technology was a spinoff of the Robonaut 2 (R2), the first humanoid robot in space. This wearable device allows the user to tightly grip tools and other items for longer periods of time without experiencing muscle discomfort or strain. An astronaut working in a pressurized suit outside the space station or an assembly operator in a factory might need to use 15 to 20 lbs of force to hold a tool during an operation. Use of the Robo-Glove, however, would potentially reduce the applied force to only 5 to 10 lbs. The Robo-Glove is a self-contained unit, essentially a robot on your hand, with actuators embedded into the glove that provide grasping support to human fingers. The pressure sensors, similar to the sensors that give R2 its sense of touch, are incorporated into the fingertips of the glove to detect when the user is grasping an object. When the user grasps the object, the synthetic tendons automatically retract, pulling the fingers into a gripping position and holding them there until the sensor is released by releasing the object. The current prototype weighs around two pounds, including control electronics and a small display for programming and diagnostics. A lithium-ion battery, such as one for power tools, is used to power the system and is worn separately on the belt.

NASA is currently developing the next generation space suit for future missions, including the optimization of space suit gloves. When non-assisted space suit gloves are coupled to a pressurized suit and operated in a vacuum, they tend to limit the range of motion of an astronaut's hand to as little as 20% of normal range. Many of NASA's future missions will be in challenging environments where an astronaut’s hand dexterity will be critical for the success of NASA missions. Innovators at JSC have improved the performance on the second-generation, robotically assisted SSRG, to reduce exertion and improve the hand strength and dexterity of an astronaut in situ. The SSRG’s system detects user finger movements using string potentiometers and contact with objects using force-sensitive resistors (FSRs). FSRs are imbedded in the distal and medial phalanges, palmar side of the glove. To move a finger, an actuator pulls a tendon through a Bowden Cable system which transfers mechanical pulling force of an inner cable relative to a hollow outer cable, like the brakes on a bicycle, as seen in the Figure below. An improved controller commands the new, more powerful linear actuator to drive tendon operation while minding custom controller parameters inputted through a digital editor tool. The Space Suit RoboGlove is at TRL 6 (system/subsystem model or prototype demonstrated in a relevant environment) and it is now available for licensing. Please note that NASA does not manufacture products itself for commercial sale.

The current Star Tracker software package is comprised of a Lumenera LW230 monochrome machine-vision camera and a FUJINON HF35SA-1 35mm lens. The star tracker cameras are all connected to and powered by the PC/104 stack via USB 2.0 ports. The software code is written in C++ and is can easily be adapted to other camera and lensing platforms by setting new variables in the software for new focal conditions. In order to identify stars in images, the software contains a star database derived from the 118,218-star Hipparcos catalog [1]. The database contains a list of every star pair within the camera field of view and the angular distance between those pairs. It also contains the inertial position information for each individual star directly from the Hipparcos catalog. In order to keep the star database size small, only stars of magnitude 6.5 or brighter were included. The star tracking process begins when image data is retrieved by the software from the data buffers in the camera. The image is translated into a binary image via a threshold brightness value so that on (bright) pixels are represented by 1s and off (dark) pixels are represented by 0s. The binary image is then searched for blobs, which are just connected groups of on pixels. These blobs represent unidentified stars or other objects such as planets, deep sky objects, other satellites, or noise. The centroids of the blob locations are computed, and a unique pattern recognition algorithm is applied to identify which, if any, stars are represented. During this process, false stars are effectively removed and only repeatedly and uniquely identifiable stars are stored. After stars are identified, another algorithm is applied on their position information to determine the attitude of the satellite. The attitude is computed as a set of Euler angles: right ascension (RA), declination (Dec), and roll. The first two Euler angles are computed by using a linear system that is derived from vector algebra and the information of two identified stars in the image. The roll angle is computed using an iterative method that relies on the information of a single star and the first two Euler angles. [1] ESA, 1997, The Hipparcos and Tycho Catalogues, ESA SP-1200

The goal of COTSAT as a technology demonstration unit is to demonstrate the ability for drastic cost reduction in spacecraft design and to develop methods and technologies for maximizing reuse of developed spacecraft hardware, software and related technology on future missions. This approach will enable for rapid response capabilities given advances in rapid prototyping. COTSAT consists of the following sub-systems: - An artificial environment container, which comprises much of the satellite structure, is used to contain the single atmosphere environment. The artificial atmosphere container is used to replicate an Earth-like atmosphere, allowing the use of Commercial-Off-The Shelf (COTS) hardware and electronics which were not necessarily originally designed to operate in the vacuum environment of space. - A key design element in the bus structure of COTSAT is the modular platform upon which the bus is assembled. This structure allows for a logic-flow integration of components leading to ideal placement of electronics. - The Electrical Power System (EPS) architecture utilizes a distributed power and self-monitor approach. - The Command and Data Handling (C&DH) subsystem provides a number of critical capabilities, including spacecraft health and status monitoring, communication, payload science data management and subsystem management. - The COTSAT communications architecture incorporates four independent communications paths. - The software architecture consists of modular, independent software daemons for each subsystem or capability such as the star tracker, the Inertial Measurement Unit (IMU), the reaction wheels, the main executive, the communications system, the control system and the payload. - The COTSAT has a three-axis Attitude Determination And Control System (ADACS), using four reaction wheels and three magnetic torque coils. - To aid in technology development and testing, the COTSAT hardware and technology performance has been verified by a number of prototype test-beds. There have been three major test platforms during the development cycle.

The key to ElectroMagnets, and Resonant Inductive Coupling (MEMRIC) is the use of low-power electromagnets for relative motion control, a magnetometer for relative distance determination, and a resonant inductive coupling system for power sharing. Traditional satellite buses house all of the major subsystems in one package. Nanosat clustering allows for the distribution of subsystems; each nanosat housing a specific subsystem (functional fractionation). MEMRIC makes this type of clustering possible, allowing a collection of system-specific nanosats to serve as a set of basic functional building blocks. Power collection, communication, navigation, computational, and propulsion units can all be combined to meet various mission requirements, greatly reducing the need for non-recurring design efforts. As new technologies for power, communications, and computation become available, these technologies can be incorporated into standardized nanosat units without the need for redesigning the other units or an entire system. Thus, the capabilities of spacecraft clusters composed of MEMRIC-enabled nanosats can evolve at the pace of technology, without incurring the large costs inherent to redesign of large, complex spacecraft.

Many control problems can benefit from the adaptive control algorithm described. This algorithm is well-suited to nonlinear applications that have unknown modeling parameters and poorly known operating conditions. Disturbance accommodation is a critical component of many systems. By using feedback control with disturbance accommodation, system performance and reliability can be increased considerably. Often the form of the disturbance is known, but the amplitude is unknown. For instance, a motor operating on a structure used for accurate pointing would cause a sinusoidal disturbance of a known frequency content. The algorithm described is able to accurately cancel these disturbances, without needing knowledge of their amplitude. In markets needing controllers, the efficiency, uptime, and lifespan of equipment can be dramatically increased due to the robustness of this technologys design.

The MAchine learning ESTimations for uRban Operations (MAESTRO) system is a novel approach that couples commodity sensors with advanced algorithms to provide real-time onboard local wind and kinematics estimations to a vehicle's guidance and navigation system. Sensors and computations are integrated in a novel way to predict local winds and promote safe operations in dynamic urban regions where Global Positioning System/Global Navigation Satellite System (GPS/GNSS) and other network communications may be unavailable or are difficult to obtain when surrounded by tall buildings due to multi-path reflections and signal diffusion. The system can be implemented onboard an Unmanned Aerial Systems (UAS) and once airborne, the system does not require communication with an external data source or the GPS/GNSS. Estimations of the local winds (speed and direction) are created using inputs from onboard sensors that scan the local building environment. This information can then be used by the onboard guidance and navigation system to determine safe and energy-efficient trajectories for operations in urban and suburban settings. The technology is robust to dynamic environments, input noise, missing data, and other uncertainties, and has been demonstrated successfully in lab experiments and computer simulations.