NASA Automated Rendezvous and Capture Review. Executive summary

In support of the Cargo Transfer Vehicle (CTV) Definition Studies in FY-92, the Advanced Program Development division of the Office of Space Flight at NASA Headquarters conducted an evaluation and review of the United States capabilities and state-of-the-art in Automated Rendezvous and Capture (AR&C). This review was held in Williamsburg, Virginia on 19-21 Nov. 1991 and included over 120 attendees from U.S. government organizations, industries, and universities. One hundred abstracts were submitted to the organizing committee for consideration. Forty-two were selected for presentation. The review was structured to include five technical sessions. Forty-two papers addressed topics in the five categories below: (1) hardware systems and components; (2) software systems; (3) integrated systems; (4) operations; and (5) supporting infrastructure

Robot Composite Learning and the Nunchaku Flipping Challenge

Advanced motor skills are essential for robots to physically coexist with humans. Much research on robot dynamics and control has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous manner, robot learning from human demonstration (LfD) has achieved great progress, but still has limitations handling dynamic skills and compound actions. In this paper, we present a composite learning scheme which goes beyond LfD and integrates robot learning from human definition, demonstration, and evaluation. The method tackles advanced motor skills that require dynamic time-critical maneuver, complex contact control, and handling partly soft partly rigid objects. We also introduce the "nunchaku flipping challenge", an extreme test that puts hard requirements to all these three aspects. Continued from our previous presentations, this paper introduces the latest update of the composite learning scheme and the physical success of the nunchaku flipping challenge

ISAR Autofocus Imaging Algorithm for Maneuvering Targets Based on Phase Retrieval and Gabor Wavelet Transform

The imaging issue of a rotating maneuvering target with a large angle and a high translational speed has been a challenging problem in the area of inverse synthetic aperture radar (ISAR) autofocus imaging, in particular when the target has both radial and angular accelerations. In this paper, on the basis of the phase retrieval algorithm and the Gabor wavelet transform (GWT), we propose a new method for phase error correction. The approach first performs the range compression on ISAR raw data to obtain range profiles, and then carries out the GWT transform as the time-frequency analysis tool for the rotational motion compensation (RMC) requirement. The time-varying terms, caused by rotational motion in the Doppler frequency shift, are able to be eliminated at the selected time frame. Furthermore, the processed backscattered signal is transformed to the one in the frequency domain while applying the phase retrieval to run the translational motion compensation (TMC). Phase retrieval plays an important role in range tracking, because the ISAR echo module is not affected by both radial velocity and the acceleration of the target. Finally, after the removal of both the rotational and translational motion errors, the time-invariant Doppler shift is generated, and radar returned signals from the same scatterer are always kept in the same range cell. Therefore, the unwanted motion effects can be removed by applying this approach to have an autofocused ISAR image of the maneuvering target. Furthermore, the method does not need to estimate any motion parameters of the maneuvering target, which has proven to be very effective for an ideal range–Doppler processing. Experimental and simulation results verify the feasibility of this approach

NASA Automated Rendezvous and Capture Review. A compilation of the abstracts

This document presents a compilation of abstracts of papers solicited for presentation at the NASA Automated Rendezvous and Capture Review held in Williamsburg, VA on November 19-21, 1991. Due to limitations on time and other considerations, not all abstracts could be presented during the review. The organizing committee determined however, that all abstracts merited availability to all participants and represented data and information reflecting state-of-the-art of this technology which should be captured in one document for future use and reference. The organizing committee appreciates the interest shown in the review and the response by the authors in submitting these abstracts

Space Applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS), phase 2. Volume 1: Telepresence technology base development

The field of telepresence is defined, and overviews of those capabilities that are now available, and those that will be required to support a NASA telepresence effort are provided. Investigation of NASA's plans and goals with regard to telepresence, extensive literature search for materials relating to relevant technologies, a description of these technologies and their state of the art, and projections for advances in these technologies over the next decade are included. Several space projects are examined in detail to determine what capabilities are required of a telepresence system in order to accomplish various tasks, such as servicing and assembly. The key operational and technological areas are identified, conclusions and recommendations are made for further research, and an example developmental program is presented, leading to an operational telepresence servicer

Autonomous flight and remote site landing guidance research for helicopters

Automated low-altitude flight and landing in remote areas within a civilian environment are investigated, where initial cost, ongoing maintenance costs, and system productivity are important considerations. An approach has been taken which has: (1) utilized those technologies developed for military applications which are directly transferable to a civilian mission; (2) exploited and developed technology areas where new methods or concepts are required; and (3) undertaken research with the potential to lead to innovative methods or concepts required to achieve a manual and fully automatic remote area low-altitude and landing capability. The project has resulted in a definition of system operational concept that includes a sensor subsystem, a sensor fusion/feature extraction capability, and a guidance and control law concept. These subsystem concepts have been developed to sufficient depth to enable further exploration within the NASA simulation environment, and to support programs leading to the flight test

A Weak Target Detection Algorithm IAR-STFT Based on Correlated K-distribution Sea Clutter Model

The detection performance of weak target on sea is affected by the special effects of sea clutter amplitude. Aiming at the time and space correlated of sea clutter, the correlated K-distribution sea clutter model is established by the sphere invariant random process algorithm. To solve the problems of range migration (RM) and Doppler frequency migration (DFM) of moving target in the case of long-time coherent accumulation, a novel integration detection algorithm, improved axis rotation short-time Fourier transform (IAR-STFT) is proposed in this paper, which is based on a generalization of traditional Fourier transform (FT) algorithm and combined with improved axis rotation. IAR-STFT not only can eliminate the RM effect by searching for the target motion parameters, but also can divide the non-stationary echo signal without range migration into several blocks. Each block of signal can be regarded as a stationary signal without DFM and FFT is performed on each signal separately. The signals of each block are accumulated to detect the target in the background of the above sea clutter. Finally, the effectiveness of the algorithm is verified by simulation. The results show that the detection ability of this algorithm is better than that of Radon-fractional Fourier transform, generalized Radon Fourier transform and Radon-Lv's distribution in low SNR environment, e.g., when the SNR is -45dB, the detection ability of this algorithm is about 55%, which is higher than that of Radon-fractional Fourier transform, generalized Radon Fourier transform and Radon-Lv's distribution