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Pomerantz, Marc

Publications and source records attributed to Pomerantz, Marc.

13 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

High Performance, Web-Based, Real-Time Telemetry Visualization for Deep Space Mission Support and Operations

The Jet Propulsion Laboratory’s Mission ControlSystems Section and Mobility and Robotic Systems Section havepartnered to developed a high-performance telemetry visualizationsystem, based on our mature, web-based, 3D visualizationsoftware technology, that provides mission trajectory designers,operations personnel and reconstruction analysts with a highlyaccurate, re-usable, multi-mission solution to interactively visualizeresults from Entry, Descent and Landing (EDL) simulations,real-time mission test beds, live telemetry streams during criticalmission events, such as landing, as well as post-event reconstructionanalysis. This work builds on previous mission visualizationsystems that we have deployed for a variety of flight missions andJPL organizations including NASA’s Mars Science Laboratory(MSL), NASA’S Low Density Supersonic Decelerator (LDSD),NASA’s Soil Moisture Active Passive (SMAP), JPL’s MoonRiseLunar sample return proposal. JPL’s mission design teams, JPL’sOffice of Naval Research tasks, and JPL’s Education and PublicOutreach Office.

Wenzel, Sean↗
NASA NTRS2017

CARACaS multi-agent maritime autonomy for unmanned surface vehicles in the Swarm II harbor patrol demonstration

This paper describes new autonomy technology that enabled a team of unmanned surface vehicles (USVs) to execute cooperative behaviors in the USV Swarm II harbor patrol demonstration and provides a description of autonomy performance in the event. The new developments extend the NASA Jet Propulsion Laboratory’s CARACaS (Control Architecture for Robotic Agent Command and Sensing) autonomy architecture, which pro- vides foundational software infrastructure, core executive functions, and several default robotic technology mod- ules. In Swarm II, CARACaS demonstrated higher levels of autonomy and more complex cooperation than previous on-water exercises, using full-sized vehicles and real-world sensing and communication. The core au- tonomous behaviors to support the harbor patrol scenario included Patrol, Track, Inspect, and Trail, providing the capability of finding all vessels entering the patrol area, keeping track of them, inspecting them to infer intent, and trailing suspect vessels. Significantly, CARACaS assumed responsibility for not only executing tasks safely and efficiently but also recognizing what tasks needed to be accomplished, given the current state of the world. Since the heterogeneous USV teams shared world model that evolved, such as due to (dis)appearance of vessels in the area or a change in health or availability of a USV, CARACaS replanned to generate and reallocate the new task list. Thus, human intervention was never required in the loop to task USVs during mission execution, though a supervisory role was supported in the autonomy system for mission monitoring and exception handling. Finally, CARACaS also ensured the USVs avoided hazards and obeyed the applicable rules of the road, using its local motion planning modules.

Sandoval, Michael↗
NASA NTRS2015

Message Brokering Evaluation for Live Spacecraft Telemetry Monitoring, Recorded Playback, and Analysis

Live monitoring and post-flight analysis of telemetry data play a vital role in the development, diagnosis, and deployment of components of a space flight mission. Requirements for such a system include low end-to-end latency between data producers and visualizers, preserved ordering of messages, data stream archiving with random access playback, and real-time creation of derived data streams. We evaluate the RabbitMQ and Kafka message brokering systems, on how well they can enable a real-time, scalable, and robust telemetry framework that delivers telemetry data to multiple clients across heterogeneous platforms and flight projects. In our experiments using an actively developed robotic arm testbed, Kafka yielded a much higher message throughput rate and a consistent publishing rate across the number of topics and consumers. Consumer message rates were consistent across the number of topics but can exhibit bursty behavior with an increase in the contention for a single topic partition with increasing number of consumers.

Lee, Daren↗
NASA NTRS2015

Applied Multi-Mission Telemetry Processing and Display for Operations, Integration, Training, Playback and Event Reconstruction

Conveying spacecraft health and status information to mission engineering personnel during various mission phases, including mission operations, is a requirement to achieve a successful mission. For NASA/JPL spacecraft, that often means displaying hundreds of telemetry channels from a variety of sensors and components emitting data at rates varying from 1hz-100hz (and faster) in a way that allows the operations team to quickly evaluate the health of the vehicle, identify any off-nominal states and resolve any issues. In this paper we will discuss the system design, requirements and use cases of three telemetry processing and visualization systems recently developed and deployed by our team for NASA's Low Density Supersonic Decelerator (LDSD) test vehicle, NASA's Soil Moisture Active/Passive (SMAP) orbiter, and JPL's Sampling Lab Universal Robotic Manipulator (SLURM) test bed.

simulation↗
NASA NTRS2015

Analyzing Cyber Security Threats on Cyber-Physical Systems Using Model-Based Systems Engineering

The spectre of cyber attacks on aerospace systems can no longer be ignored given that many of the components and vulnerabilities that have been successfully exploited by the adversary on other infrastructures are the same as those deployed and used within the aerospace environment. An important consideration with respect to the mission/safety critical infrastructure supporting space operations is that an appropriate defensive response to an attack invariably involves the need for high precision and accuracy, because an incorrect response can trigger unacceptable losses involving lives and/or significant financial damage. A highly precise defensive response, considering the typical complexity of aerospace environments, requires a detailed and well-founded understanding of the underlying system where the goal of the defensive response is to preserve critical mission objectives in the presence of adversarial activity. In this paper, a structured approach for modeling aerospace systems is described. The approach includes physical elements, network topology, software applications, system functions, and usage scenarios. We leverage Model-Based Systems Engineering methodology by utilizing the Object Management Group's Systems Modeling Language to represent the system being analyzed and also utilize model transformations to change relevant aspects of the model into specialized analyses. A novel visualization approach is utilized to visualize the entire model as a three-dimensional graph, allowing easier interaction with subject matter experts. The model provides a unifying structure for analyzing the impact of a particular attack or a particular type of attack. Two different example analysis types are demonstrated in this paper: a graph-based propagation analysis based on edge labels, and a graph-based propagation analysis based on node labels.

MBSE↗
NASA NTRS2006

Generating CAHV and CAHVOR Images with Shadows in ROAMS

Part of the Rover Analysis, Modeling and Simulation (ROAMS) software that synthesizes images of terrain has been augmented to make the images more realistic. [ROAMS was described in "Simulating Operation of a Planetary Rover" (NPO-30722), NASA Tech Briefs, Vol. 28, No. 9 (September 2004), page 52. ROAMS simulates the operation of a robotic vehicle (rover) exploring terrain on a remote planet.] The images are needed for modeling responses of rover cameras that provide sensory inputs for machine-vision-based algorithms for controlling the motion of the rover. The augmented image-synthesizing part of the ROAMS software supports terrain geometry and texture specifiable by the user, CAHV and CAHVOR camera models, and more-realistic shadowing (see figure). (The letters in "CAHV" represent vectors in a standard photogrammetric model of a pinhole camera. Letters O and R in "CAHVOR" represent vectors used to model distortions.) A contemplated future version of ROAMS would support the CAHVORE model, which represents more-general cameras, including those having fish-eye or other wide-field-of-view lenses. (Letter E in "CAHVORE" represents a vector used to model apparent motion of a camera entrance pupil.)

Madison, Richard↗