Engineering topics

Robinson, Shane

Publications and source records attributed to Robinson, Shane.

10 records

NASA NTRS2018

Orion's Powered Flight Guidance Burn Options for Near Term Exploration Missions

NASA's Orion exploration spacecraft will fly more demanding mission profiles than previous NASA human flight spacecraft. Missions currently under development are destined for cislunar space. The EM-1 mission will fly unmanned to a Distant Retrograde Orbit (DRO) around the Moon. EM-2 will fly astronauts on a mission to the lunar vicinity. To fly these missions, Orion requires powered flight guidance that is more sophisticated than the orbital guidance flown on Apollo and the Space Shuttle. Orion's powered flight guidance software contains five burn guidance options. These five options are integrated into an architecture based on a proven shuttle heritage design, with a simple closed-loop guidance strategy. The architecture provides modularity, simplicity, versatility, and adaptability to future, yet-to-be-defined, exploration mission profiles. This paper provides a summary of the executive guidance architecture and details the five burn options to support both the nominal and abort profiles for the EM-1 and EM-2 missions.

Fill, Thomas↗

NASA NTRS2018

Orion Powered Flight Guidance Burn Options for Near Term Exploration

Fill, Tom↗

NASA NTRS2016

Visual Odometry for Autonomous Deep-Space Navigation Project

Autonomous rendezvous and docking (AR&D) is a critical need for manned spaceflight, especially in deep space where communication delays essentially leave crews on their own for critical operations like docking. Previously developed AR&D sensors have been large, heavy, power-hungry, and may still require further development (e.g. Flash LiDAR). Other approaches to vision-based navigation are not computationally efficient enough to operate quickly on slower, flight-like computers. The key technical challenge for visual odometry is to adapt it from the current terrestrial applications it was designed for to function in the harsh lighting conditions of space. This effort leveraged Draper Laboratory’s considerable prior development and expertise, benefitting both parties. The algorithm Draper has created is unique from other pose estimation efforts as it has a comparatively small computational footprint (suitable for use onboard a spacecraft, unlike alternatives) and potentially offers accuracy and precision needed for docking. This presents a solution to the AR&D problem that only requires a camera, which is much smaller, lighter, and requires far less power than competing AR&D sensors. We have demonstrated the algorithm’s performance and ability to process ‘flight-like’ imagery formats with a ‘flight-like’ trajectory, positioning ourselves to easily process flight data from the upcoming ‘ISS Selfie’ activity and then compare the algorithm’s quantified performance to the simulated imagery. This will bring visual odometry beyond TRL 5, proving its readiness to be demonstrated as part of an integrated system.Once beyond TRL 5, visual odometry will be poised to be demonstrated as part of a system in an in-space demo where relative pose is critical, like Orion AR&D, ISS robotic operations, asteroid proximity operations, and more.

Robinson, Shane↗

NASA NTRS2016

Visual Odometry for Autonomous Deep-Space Navigation Project

Autonomous rendezvous and docking (AR&D) is a critical need for manned spaceflight, especially in deep space where communication delays essentially leave crews on their own for critical operations like docking. Previously developed AR&D sensors have been large, heavy, power-hungry, and may still require further development (e.g. Flash LiDAR). Other approaches to vision-based navigation are not computationally efficient enough to operate quickly on slower, flight-like computers. The key technical challenge for visual odometry is to adapt it from the current terrestrial applications it was designed for to function in the harsh lighting conditions of space. This effort leveraged Draper Laboratory's considerable prior development and expertise, benefitting both parties. The algorithm Draper has created is unique from other pose estimation efforts as it has a comparatively small computational footprint (suitable for use onboard a spacecraft, unlike alternatives) and potentially offers accuracy and precision needed for docking. This presents a solution to the AR&D problem that only requires a camera, which is much smaller, lighter, and requires far less power than competing AR&D sensors. We have demonstrated the algorithm's performance and ability to process 'flight-like' imagery formats with a 'flight-like' trajectory, positioning ourselves to easily process flight data from the upcoming 'ISS Selfie' activity and then compare the algorithm's quantified performance to the simulated imagery. This will bring visual odometry beyond TRL 5, proving its readiness to be demonstrated as part of an integrated system. Once beyond TRL 5, visual odometry will be poised to be demonstrated as part of a system in an in-space demo where relative pose is critical, like Orion AR&D, ISS robotic operations, asteroid proximity operations, and more.

Robinson, Shane↗

NASA NTRS2016

Visual Odometry for Autonomous Deep-Space Navigation

Visual Odometry fills two critical needs shared by all future exploration architectures considered by NASA: Autonomous Rendezvous and Docking (AR&D), and autonomous navigation during loss of comm. To do this, a camera is combined with cutting-edge algorithms (called Visual Odometry) into a unit that provides accurate relative pose between the camera and the object in the imagery. Recent simulation analyses have demonstrated the ability of this new technology to reliably, accurately, and quickly compute a relative pose. This project advances this technology by both preparing the system to process flight imagery and creating an activity to capture said imagery. This technology can provide a pioneering optical navigation platform capable of supporting a wide variety of future missions scenarios: deep space rendezvous, asteroid exploration, loss-of-comm.

Robinson, Shane↗

NASA NTRS2016

Orion Burn Management, Nominal and Response to Failures

An approach for managing Orion on-orbit burn execution is described for nominal and failure response scenarios. The burn management strategy for Orion takes into account per-burn variations in targeting, timing, and execution; crew and ground operator intervention and overrides; defined burn failure triggers and responses; and corresponding on-board software sequencing functionality. Burn-to- burn variations are managed through the identification of specific parameters that may be updated for each progressive burn. Failure triggers and automatic responses during the burn timeframe are defined to provide safety for the crew in the case of vehicle failures, along with override capabilities to ensure operational control of the vehicle. On-board sequencing software provides the timeline coordination for performing the required activities related to targeting, burn execution, and responding to burn failures.

Odegard, Ryan↗

NASA NTRS2016

Observations of the Geometry of Horizon-Based Optical Navigation

NASA's Orion Project has sparked a renewed interest in horizon-based optical navigation(OPNAV) techniques for spacecraft in the Earth-Moon system. Some approaches have begun to explore the geometry of horizon-based OPNAV and exploit the fact that it is a conic section problem. Therefore, the present paper focuses more deeply on understanding and leveraging the various geometric interpretations of horizon-based OPNAV. These results provide valuable insight into the fundamental workings of OPNAV solution methods, their convergence properties, and associated estimate covariance. Most importantly, the geometry and transformations uncovered in this paper lead to a simple and non-iterative solution to the generic horizon-based OPNAV problem. This represents a significant theoretical advancement over existing methods. Thus, we find that a clear understanding of geometric relationships is central to the prudent design, use, and operation of horizon-based OPNAV techniques.

Christian, John↗

NASA NTRS2016

Encke-Beta Predictor for Orion Burn Targeting and Guidance

The state vector prediction algorithm selected for Orion on-board targeting and guidance is known as the Encke-Beta method. Encke-Beta uses a universal anomaly (beta) as the independent variable, valid for circular, elliptical, parabolic, and hyperbolic orbits. The variable, related to the change in eccentric anomaly, results in integration steps that cover smaller arcs of the trajectory at or near perigee, when velocity is higher. Some burns in the EM-1 and EM-2 mission plans are much longer than burns executed with the Apollo and Space Shuttle vehicles. Burn length, as well as hyperbolic trajectories, has driven the use of the Encke-Beta numerical predictor by the predictor/corrector guidance algorithm in place of legacy analytic thrust and gravity integrals.

Robinson, Shane↗

NASA NTRS2015

Advances in Orion's On-Orbit Guidance and Targeting System Architecture

NASA's manned spaceflight programs have a rich history of advancing onboard guidance and targeting technology. In order to support future missions, the guidance and targeting architecture for the Orion Multi-Purpose Crew Vehicle must be able to operate in complete autonomy, without any support from the ground. Orion's guidance and targeting system must be sufficiently flexible to easily adapt to a wide array of undecided future missions, yet also not cause an undue computational burden on the flight computer. This presents a unique design challenge from the perspective of both algorithm development and system architecture construction. The present work shows how Orion's guidance and targeting system addresses these challenges. On the algorithm side, the system advances the state-of-the-art by: (1) steering burns with a simple closed-loop guidance strategy based on Shuttle heritage, and (2) planning maneuvers with a cutting-edge two-level targeting routine. These algorithms are then placed into an architecture designed to leverage the advantages of each and ensure that they function in concert with one another. The resulting system is characterized by modularity and simplicity. As such, it is adaptable to the on-orbit phases of any future mission that Orion may attempt.

Scarritt, Sara K.↗

NASA NTRS2011

Development of Tools and Techniques for Processing STORRM Flight Data

While at JSC for the summer of 2011, I was assigned to work on the sensor test for Orion relative-navigation risk mitigation (STORRM) development test objective (DTO). The STORRM DTO was flown on-board Endeavor during STS-134. The objective of the STORRM DTO is to test the visual navigation system (VNS), which will be used as the primary relative navigation sensor for the Orion spacecraft. The VNS is a flash lidar system intended to provide both line of sight and range information during rendezvous and proximity operations. The STORRM DTO also serves as a testbed for the high-resolution docking camera. This docking camera will be used to provide piloting cues for the crew during proximity operations. These instruments were mounted next to the trajectory control sensor (TCS) in Endeavour s payload bay. My principle objective for the summer was to generate a best estimated trajectory (BET) for Endeavor using the flight data collected by the VNS during rendezvous and the unprecedented re-rendezvous with the ISS. I processed the raw images from the VNS to produce range and bearing measurements. I then aggregated these measurements and extracted the measurements corresponding to individual reflectors. I combined the information contained in these measurements with data from the Endeavour's inertial sensors using Kalman smoothing techniques to ultimately produce a BET. This work culminated with a final presentation of the result to division management. Development of this tool required that traditional linear smoothing techniques be modified in a novel fashion to permit for the inclusion of non-linear measurements. This internship has greatly helped me further my career by providing exposure to real engineering projects. I also have benefited immensely from the mentorship of the engineers working on these projects. Many of the lessons I learned and experiences I had are of particular value because then can only be found in a place like JSC.

Robinson, Shane↗