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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Milli-Watt Radioisotope Power to Enable Small, Long-Term Robotic “Probe” Space Exploration

Milli-watt Radioisotope Power Systems (RPS) based on Radioisotope Heater Units (RHUs) could be an ideal power source for certain spacecraft that cannot use solar power due to large distances from the sun, or other environmental constraints, and where they enable or significantly enhance the ability of a mission to meet its scientific or operational goals. Various modular, compact RHU-based thermoelectric (TE) generator concepts developed or derived from current NASA Small Business Innovation Research (SBIR) projects satisfying this need have been investigated. These modular, compact and low mass power systems could support small, highly-mobile robotic exploration packages, and could be incorporated into different robotic package concepts, spacecraft or satellites. Current modular RPS design concepts with 40mW, 80mW and 120mW power levels use RHUs and Bi2Te3 TE converters. Skutterudites materials could be used in the future if new higher thermal energy output and higher temperature miniature heat sources were developed, for example, using technologies currently in the General Purpose Heat Source (GPHS) used in higher electric power output RTGs. Small (a.k.a., “mice-like”) robotic packages could effectively utilize these RHU-driven power levels to accommodate crawling, climbing, monitoring, taking measurements, and communicating during long-term planetary missions aimed at gathering environmental and geologic data (i.e., over multiple decades). Waste heat from the cold side of the TE converter could also be directed toward the electronics and / or energy storage (e.g. batteries) to keep them within design temperature ranges. In addition to power generation and electronics / battery heating, the RHU / TE configuration could be designed to survive an external 500°C bake out procedure for critical spacecraft sterilization, environmental certification and planetary protection. Analytical studies have been performed to optimize various design configurations for power, mass, volume and robotic mobility. Specific power (mW/kg) and volumetric specific power (mW/cm3) characteristics of various design configurations will be presented and key conceptual design tradeoffs will be discussed. Hot- and cold-side thermal interfaces required to meet power and mass goals and associated design sensitivities will also be discussed. RHU / TE systems must overcome critical design challenges to survive high-g loadings in some robotic applications and we will examine the mass impacts required to satisfy various dynamic loading environments up to 10,000 g’s. Power can be generated for a minimum of 30 years or more using plutonium-238 dioxide heat sources (given that Pu-238 has an 87.7 year half-life) with some reduction in power as the heat source naturally degrades.

Bahrami, Poyan↗
NASA NTRS1988

Robotic applications at Kennedy Space Center

McDonnell Douglas performed a study (1987) to find effective application of robots and their associated technology at the Kennedy Space Center (KSC). Specifically, this study was directed toward the newly planned Space Station Processing Facility (SSPF). Because the Operations and Checkout (O and C) building has a similar charter to that of the SSPF, the O and C was carefully checked for potential robotic applications. Eleven applications were discovered and a trade study developed to rate these applications. Twenty more applications external to the SSPF were found during additional studies. These robotic tasks fall into three major categories including: teleoperated robots for hazardous tasks, mobile robots for repetitive tasks and feedback compensated robots for refurbishment and inspection tasks. This paper highlights some of the requirements for these tasks and others external to the SSPF. Additionally, the resources available at KSC are discussed.

Wegerif, Dan↗
NASA NTRS1991

Telerobotic control of a mobile coordinated robotic server

Results from the Master's Degree Thesis of Mr. Robert Stanley, a graduate student supervised by the principal investigator on this project is reported. The goal of this effort is to develop advanced control methods for flexible space manipulator systems. As such, a fuzzy logic controller has been developed in which model structure as well as parameter constraints are not required for compensation. A general rule base is formulated using quantized linguistic terms; it is then augmented to a traditional integral control. The resulting hybrid fuzzy controller stabilizes the structure over a broad range of uncertainties, including unknown initial conditions. An off-line tuning approach using phase portraits gives further insight into the algorithm. The approach was applied to a three-degree-of-freedom manipulator system - the prototype of the coordinated flexible manipulator system currently being designed and built at North Carolina State University.

Lee, Gordon↗
NASA NTRS1993

Telerobotic control of a mobile coordinated robotic server, executive summary

This interim report continues with the research effort on advanced adaptive controls for space robotics systems. In particular, previous results developed by the principle investigator and his research team centered around fuzzy logic control (FLC) in which the lack of knowledge of the robotic system as well as the uncertainties of the environment are compensated for by a rule base structure which interacts with varying degrees of belief of control action using system measurements. An on-line adaptive algorithm was developed using a single parameter tuning scheme. In the effort presented, the methodology is further developed to include on-line scaling factor tuning and self-learning control as well as extended to the multi-input, multi-output (MIMO) case. Classical fuzzy logic control requires tuning input scale factors off-line through trial and error techniques. This is time-consuming and cannot adapt to new changes in the process. The new adaptive FLC includes a self-tuning scheme for choosing the scaling factors on-line. Further the rule base in classical FLC is usually produced by soliciting knowledge from human operators as to what is good control action for given circumstances. This usually requires full knowledge and experience of the process and operating conditions, which limits applicability. A self-learning scheme is developed which adaptively forms the rule base with very limited knowledge of the process. Finally, a MIMO method is presented employing optimization techniques. This is required for application to space robotics in which several degrees-of-freedom links are commonly used. Simulation examples are presented for terminal control - typical of robotic problems in which a desired terminal point is to be reached for each link. Future activities will be to implement the MIMO adaptive FLC on an INTEL microcontroller-based circuit and to test the algorithm on a robotic system at the Mars Mission Research Center at North Carolina State University.

Lee, Gordon↗
NASA NTRS2018

Surrogate: A Body-Dexterous Mobile Manipulation Robot with a Tracked Base

Robotics platforms in accordance with various embodiments of the invention can be utilized to implement highly dexterous robots capable of whole body motion. Robotics platforms in accordance with one embodiment of the invention include: a memory containing a whole body motion application; a spine, where the spine has seven degrees of freedom and comprises a spine actuator and three spine elbow joints that each include two spine joint actuators; at least one limb, where the at least one limb comprises a limb actuator and three limb elbow joints that each include two limb joint actuators; a tracked base; a connecting structure that connects the at least one limb to the spine; a second connecting structure that connects the spine to the tracked base; wherein the processor is configured by the whole body motion application to move the at least one limb and the spine to perform whole body motion.

Kennedy, Brett A.↗
NASA NTRS2003

Hopping Robot with Wheels

A small prototype mobile robot is capable of (1) hopping to move rapidly or avoid obstacles and then (2) moving relatively slowly and precisely on the ground by use of wheels in the manner of previously reported exploratory robots of the "rover" type. This robot is a descendant of a more primitive hopping robot described in "Minimally Actuated Hopping Robot" (NPO- 20911), NASA Tech Briefs, Vol. 26, No. 11 (November 2002), page 50. There are many potential applications for robots with hopping and wheeled-locomotion (roving) capabilities in diverse fields of endeavor, including agriculture, search-and-rescue operations, general military operations, removal or safe detonation of land mines, inspection, law enforcement, and scientific exploration on Earth and remote planets. The combination of hopping and roving enables this robot to move rapidly over very rugged terrain, to overcome obstacles several times its height, and then to position itself precisely next to a desired target. Before a long hop, the robot aims itself in the desired hopping azimuth and at a desired takeoff angle above horizontal. The robot approaches the target through a series of hops and short driving operations utilizing the steering wheels for precise positioning.

Barlow, Edward↗
NASA NTRS2001

Reconfigurable robots for all terrain exploration

While significant recent progress has been made in development of mobile robots for planetary suface exploration,there remain major challenges. These include increased autonomy of operation, traverse of challenging terrain, and fault-tolerance under long, unattended periods of use.

mobile robots multi-robot cooperation robotic arch↗
NASA NTRS1990

Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

Rodriguez, Guillermo↗
NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a mobile robotic bucket-drum excavator platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for estimating the quantity of regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete In-Situ Resource Utilization (ISRU) missions. To teleoperate or run autonomously, it is crucial for the amount of regolith mass ingested to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of the total mass in the drums, this type of high-level planning is not possible. Three distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR, none of which require modification to the hardware. All take in system states, such as arm/drum motor positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums. The developed models run in real-time, outputting predictions for the front drum mass, rear drum mass, timestamp of the last prediction, and total drum mass (sum of front and rear) in RASSOR’s drums. Models deployed to the hardware have low error (<7.5% mean error over the mass range, and <2.6% mean error when drums are more than half full) when making predictions in real-time. Our modeling approach can be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results of this work are promising and show that models can be developed to accurately estimate excavated regolith mass.

Bucket Drum Excavators↗
NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a mobile robotic bucket-drum excavator platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for estimating the quantity of regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete In-Situ Resource Utilization (ISRU) missions. To teleoperate or run autonomously, it is crucial for the amount of regolith mass ingested to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of the total mass in the drums, this type of high-level planning is not possible. Three distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR, none of which require modification to the hardware. All take in system states, such as arm/drum motor positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums. The developed models run in real-time, outputting predictions for the front drum mass, rear drum mass, timestamp of the last prediction, and total drum mass (sum of front and rear) in RASSOR’s drums. Models deployed to the hardware have low error (<7.5% mean error over the mass range, and <2.6% mean error when drums are more than half full) when making predictions in real-time. Our modeling approach can be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results of this work are promising and show that models can be developed to accurately estimate excavated regolith mass.

bucket drum excavators↗