Robotics, Automation and Control
Robotics, Automation and Control
Mechanical devices or machines that resemble a human or are designed to replace human beings semi- or fully-autonomously by performing a variety of complex or routine mechanical tasks either on command or by being programmed in advance.
Sampling and Control Circuit Board
For fast platform dynamics, it is necessary to sample the IMU at quick intervals in order to fulfill the Nyquist sampling theorem requirements. This can be difficult in cases where low size, weight, and power are required, since a primary processor may already be saturated running the navigation algorithm or other system functions. Glenn's novel circuit board was designed to handle the sampling process (involving frequent interrupt requests) in parallel, while delivering the resulting data to a buffered communication port for inclusion in the navigation algorithm on an as-available basis. The circuit operates using a universal serial bus (USB) or Bluetooth interface. A control command is sent to the circuit from a separate processor or computer that instructs the circuit how to sample data. Then, a one-pulse-per-second signal from a GPS receiver or other reliable time source is sent to trigger the circuit to perform automatic data collection from the IMU sensor. This is an early-stage technology requiring additional development. Glenn welcomes co-development opportunities.
Wireless Electrical Devices Using Floating Electrodes
The technology presents a fundamental change in the way electrical devices are designed, using an open circuit in conjunction with a floating electrode, or an electrically conductive object not connected to anything by wires, and powered through a wireless device. This system uses inductor-capacitor thin-film open circuit technology. It consists of a uniquely designed, electrically conductive geometric pattern that stores energy in both electric and magnetic fields, along with a floating electrode in proximity to the open circuit. When wirelessly pulsed from the handheld data acquisition system (U.S. Patent Number 7,159,774, Magnetic Field Response Measurement Acquisition System), the system becomes electrically active and develops a capacitance between the two circuit surfaces. The result is a device that acts as a parallel plate capacitor without electrical connections.
Robotic Assembly of Photovoltaic Arrays
NASA researchers have developed the PAPA technology to increase the efficiency of the thin-film solar array assembly process, significantly decreasing assembly time and labor costs associated with manufacturing large scale solar arrays. Traditional solar cell assembly is a labor intensive, multi-step, time-consuming process. This manual assembly will not be possible in a space environment. To enable solar array assembly in space, PAPA leverages robotic automation to distill the traditional assembly method into four fully automated steps: applying adhesive to block substrate, placing the solar cells using a vacuum tool attached to a universal robotic arm, printing the interconnects and buses to connect the cells, and applying a protective cover. The PAPA technology is compatible with a variety of thin-film solar cells, including 3D printed cells (essential for future in-space manufacturing of arrays) and terrestrial manufacturing methods. As solar cell technologies mature, PAPA will be able to incorporate advancements into the paneling process. NASA researchers have begun to employ PAPA solar array fabrication and estimate savings of $300-$400/watt. For extraterrestrial assembly of solar panels the size of a football field or larger, PAPA could result in savings of approximately $500 million; a substantial cost savings driven by standardization and efficiency in the solar array assembly process. By demonstrating increases in assembly efficiency, time and cost savings, and passing multiple environmental exposure tests, the PAPA lab protype has completed the final phases of technology development and is ready for scale-up and commercialization.
Monitoring and Control of Each Nanosatellite within a Cluster of Nanosatellites
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.
Multivariate Monitoring for Human Operator and Machine Teaming
Inventors at NASA have developed a novel approach to optimizing human machine teaming. The technology enables the inclusion of the state of the human operator in system wide prognostics for increasingly autonomous vehicles. It also could inform the design of automation and intelligent systems for low proficiency and reduced crews. The system monitors and measures multiple variables in real time, the status of the human operator and communicates that information to an intelligent machine. Status could include behavior, skill, physical or medical status, or mental state. Once this information pathway is established, the predictability of pilot or operator status will be improved so the autonomous system can be said to develop trust in human operators much like humans develop trust in automation. The system would utilize non-contact instrumentation for biosignal, posture and behavioral gesture sensing for automation decision making.
Otoacoustic Protection In Biologically-Inspired Systems
This innovation is an autonomic method capable of transmitting a neutralizing data signal to counteract a potentially harmful signal. This otoacoustic component of an autonomic unit can render a potentially harmful incoming signal inert. For selfmanaging systems, the technology can offer a selfdefense capability that brings new levels of automation and dependability to systems.
Robonaut 2: Logistics and Distribution
R2 was designed to work side-by-side with people and to be sensitive to its surroundings. The robot's advanced vision systems and recognition processing can quickly recognize a person in its path and take the appropriate action. If the robot comes into contact with a person or piece of equipment, it gives. There is no need to design specialized equipment for R2 because the robot has the ability to operate equipment and machines designed for humans, like hand-held power tools. R2 has the capability to improve the speed and accuracy of operations while maintaining sensitivity to its surroundings, making the robot prime for the logistics and distribution environment. R2 was designed to handle unexpected objects coming into its path since it has to function in space where not everything is locked down. The robot has the ability to move in unconventional ways as compared to existing robots. Robonaut 1, an earlier version of R2, was integrated with a two-wheeled Segway personal transporter, giving it a range of motion. R2 has the capability of being integrated onto a two-wheeled base or a more rugged four-wheel base. An adaptable interface would enable R2 to integrate with other surface mobility systems. This NASA Technology is available for your company to license and develop into a commercial product. NASA does not manufacture products for commercial sale.
Algorithms for stabilizing intelligent networks
Some of the current challenges faced by research in artificial intelligence and autonomous control systems include providing self control, resilience, adaptability, and stability for intelligent systems, especially over a long period of time, in changing environments. The Evolvable Neural Software System (ENSS), Formulation for Emotion Embedding in Logic Systems (FEELS), Stability Algorithm for Neural Entities (SANE), and the Logic Expansion for Autonomously Reconfigurable Neural Systems (LEARNS) are foundations for tackling some of these challenges, by providing the basic algorithms evolvable systems could use to manage its own behavior. These algorithms would allow networks to self regulate, noticing unusual behavior and the circumstances that may have caused that behavior, and then correcting to behave more predictably when similar circumstances are encountered. The process is similar to how psychology in organisms evolved iteratively, eventually finding and keeping better responses to given stimuli.
Robotic gripper for satellite capture and servicing
The Gripper is located at the end of a robotic system consisting of a robotic arm equipped with a Tool Drive or End Effector comprising the input actuator to the Gripper as well as the structural, power and data link between the Gripper and the robotic arm. In a notional concept of operations, a Servicer would approach the Client in an autonomous rendezvous and capture (AR&C) maneuver. When the Servicers sensor suite confirms that the distance, orientation, and relative translational and angular rates with respect to the Client are within an acceptable range, the Servicer enables the grasping sequence, where the robotic arm, equipped with Gripper, extend forward to the Client. When the Gripper/ Servicer sensors indicate that the Client marman ring is sufficiently within the capture range of the Gripper, a trigger signal is sent to the robot control system that commands the End Effector to drive the mechanism of the Gripper and affect closure around the marman ring. The Gripper consists of a pair of jaws which are driven by an internal transmission. The transmission receives input torque from the End Effector and converts the torque to appropriate motion of the jaws.
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