Search NASA⌕ Search

SEARCH · Search NASA

Results for “trajectory generation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Prospective Architectures for Onboard vs Cloud-Based Decision Making for Unmanned Aerial Systems

This paper investigates propsective architectures for decision-making in unmanned aerial systems. When these unmanned vehicles operate in urban environments, there are several sources of uncertainty that affect their behavior, and decision-making algorithms need to be robust to account for these different sources of uncertainty. It is important to account for several risk-factors that affect the flight of these unmanned systems, and facilitate decision-making by taking into consideration these various risk-factors. In addition, there are several technical challenges related to autonomous flight of unmanned aerial systems; these challenges include sensing, obstacle detection, path planning and navigation, trajectory generation and selection, etc. Many of these activities require significant computational power and in many situations, all of these activities need to be performed in real-time. In order to efficiently integrate these activities, it is important to develop a systematic architecture that can facilitate real-time decision-making. Four prospective architectures are discussed in this paper; on one end of the spectrum, the first architecture considers all activities/computations being performed onboard the vehicle whereas on the other end of the spectrum, the fourth and final architecture considers all activities/computations being performed in the cloud, using a new service known as Prognostics as a Service that is being developed at NASA Ames Research Center. The four different architectures are compared, their advantages and disadvantages are explained and conclusions are presented.

Software engineering↗
NASA NTRS2018

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as "Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Interplanetary↗
NASA NTRS2018

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as ``Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Napier, Sean W.↗
NASA NTRS2018

Autonomous Path-Following for a Tilt-Wing, Distributed Electric Propulsion, Vertical Take-Off and Landing Unmanned Aerial System in Hover Mode

This paper presents an autonomous path-following control architecture for a tilt-wing, distributed electric propulsion, vertical take-off and landing unmanned aerial system in hover mode and presents indoor flight test results. The test-bed vehicle is a subscale model with the same configuration as the NASA GL-10 aircraft. The control architecture consists of an inner-loop attitude controller, outer-loop trajec­tory controller, and a trajectory generation scheme. The flight test results show that the vehicle can satisfactorily follow a path prescribed by a list of waypoints around the indoor flight room.

Cooper, John R.↗
NASA NTRS2019

Exploration of Atmospheric Entries at Uranus & Neptune with HEEET as Heatshield TPS

One important observation from the recent Ice Giants Study sponsored by NASA was that the predicted and margined thicknesses of HEEET (new NASA TPS technology) were much greater than could be woven with the currently established loom capabilities. Since the cost of a loom upgrade would be substantial, the present work explores the entry trajectory space to determine what combinations of entry parameters would result in HEEET thicknesses that fit within the existing loom infrastructure. Toward this end, the entry trajectory space, parameterized by ballistic coefficient and entry flight path angle, was systematically explored for 45° sphere-cone geometries of 3 different radii 0.2 m, 0.3 m, and 0.4 m which covered the range from Galileo-derived probes considered in the Ice Giants Study, and a follow-on study on the possibility of using a single probe architecture (in terms of size and mass) for various destinations, including Venus, Saturn, Uranus, and Neptune. The entry velocities, latitudes, and azimuths at Uranus and Neptune used in the present work were taken from the Ice Giants Study. For each 3D OF trajectory generated by a NASA Ames in-house code, TRAJ, the material response and thickness were computed using another NASA Ames code, FIAT, along with a margins policy proposed by the HEEET project. In the present work, ballistic coefficients ranging from 200 kg/sqm to 350 kg/sqm were considered along with entry flight path angles ranging from -16° to -36° (primarily to allow deceleration loads to vary between 50 g and 200 g).

Prabhu, Dinesh K.↗
NASA NTRS2019

Exploration of Atmospheric Entries at Uranus & Neptune with HEEET as Heatshield TPS

One important observation from the Ice Giants Study was that the predicted and margined thicknesses of HEEET were greater than could be woven with the currently established loom capabilities. Since the cost of a loom upgrade would be substantial, the present work explored the entry trajectory space to determine what combinations of entry parameters would result in HEEET thicknesses that fit within the existing loom infrastructure. Toward this end, the entry trajectory space, parameterized by ballistic coefficient and entry flight path angle, was systematically explored for 45° sphere-cone geometries of 3 different radii – 0.2 m, 0.3 m, and 0.4 m – which covered the range from Galileo-derived probes considered in the Ice Giants Study, and a follow-on study [4] on the possibility of using a single probe architecture (in terms of size and mass) for various destinations, including Venus, Saturn, Uranus, and Neptune. The entry velocities, latitudes, and azimuths at Uranus and Neptune used in the present work were taken from the Ice Giants Study [1]. For each 3DOF trajectory generated by a NASA Ames in-house code, TRAJ [5], the material response and thickness were computed using another NASA Ames code, FIAT [6], along with a margins policy proposed by the HEEET project [7]. In the present work, ballistic coefficients ranging from 200 kg/m2 to 350 kg/m2 were considered along with entry flight path angles ranging from -16° to -36° (primarily to allow deceleration loads to vary between 50 g and 200 g).

HEEET↗
NASA NTRS2017

Autonomous Guidance Navigation and Control for Agile Quadrotors Using Polynomial Trajectory Planning and L1 Adaptive Control

We address the challenge to allow efficient autonomous flight in real world environments, both indoor and outdoor. We use a straight-line SE-SCP (Spherical Expansion and Sequential Convex Programming) [algorithm] to find an initial route through the environment and minimum snap trajectory generation using piecewise polynomials. Then, we implement an adaptive robust control able to address some robustness issues for quadrotors in outdoor flight, such as mass variation and wind disturbances. Coupling these techniques we allow high-speed and aggressive autonomous flight through obstacle-dense indoor environments, as well as address outdoor disturbances.

Landolfi, Mattia↗
NASA NTRS2019

Ballistic Entries for Saturn, Uranus, and Neptune with HEEET TPS

One important observation from the Ice Giants Study was that the predicted and margined thicknesses of HEEET were greater than could be woven with the currently established loom capabilities. Since the cost of a loom upgrade could be substantial and time consuming, the present work explored the entry trajectory space to determine what combinations of entry parameters would result in HEEET thicknesses that fit within the existing loom infrastructure. Toward this end, the entry trajectory space, parameterized by ballistic coefficient and entry flight path angle, was systematically explored for 45° sphere-cone geometries of 3 different radii – 0.2 m, 0.3 m, and 0.4 m – which covered the range from Galileo-derived probes considered in the Ice Giants Study, and a follow-on study on the possibility of using a single probe architecture (in terms of size and mass) for various destinations, including Venus, Saturn, Uranus, and Neptune. The entry velocities, latitudes, and azimuths at Uranus and Neptune used in the present work were taken from the Ice Giants Study. For each 3DOF trajectory generated by a NASA Ames in-house code, TRAJ, the material response and thickness were computed using another NASA Ames code, FIAT, along with a margins policy proposed by the HEEET project. In the present work, ballistic coefficients ranging from 200 kg/sq m to 350 kg/sq m were considered along with entry flight path angles ranging from -16° to -36° (primarily to allow deceleration loads to vary between 50 g and 200 g).

Atmospheric Entry↗
NASA NTRS2020

Robotic Assembly Activities at NASA Langley Research Center

Over the past several decades, NASA Langley Research Center (LaRC) has developed a suite of hardware and software capabilities for robotic in-space assembly. Specific robots include the Lightweight Surface Manipulation System (LSMS), Tendon-Actuated Lightweight In-Space Manipulator (TALISMAN), NASA Intelligent Jigging and Assembly Robot (NINJAR), Strut Assembly, Manufacturing, Utility & Robotic Aid (SAMURAI), and most recently the Assemblers modular robots. Alongside the hardware, software tools such as the Autonomous Entity Operations Network (AEON) and the Baseline Environment for Autonomous Modeling (BEAM) have been developed to enable communication and simulation respectively. These tools have supported foundational research in single and multi-agent control, sensing and perception, trajectory generation, task allocation, and human-machine teaming. This talk will provide a broad overview of these capabilities and go into detail on recent developments made by the Assemblers project to create modular, reconfigurable robots for autonomous in-space assembly.

John R Cooper↗
NASA NTRSDate not supplied

A Rapid Target-Search Technique for KBO Exploration Trajectories

A rapid, grid-based, target-search algorithm is presented to find candidate se-quences of small-body encounters for mission design. The algorithm is especially relevant for cases with large combinatorial spaces. In this paper, the al-gorithm is used to identify candidate flyby sequences of multiple Kuiper-Belt Ob-jects (KBOs). Before reaching the first KBO in the sequence, the trajectories in this paper first use gravity assists at one or more of the giant planets to pump-uptheir orbital energy—reducing launch C3. The target-search algorithm consists offour sequential steps: (1) parameter definition, (2) fine-tuned Lambert-based gridsearch of ballistic trajectories visiting one KBO, (3) rapid, ∆V-based proximitysearch for additional KBOs using the state transition matrices (STMs), and (4) tra-jectory optimization of the most promising KBO sequences using the EvolutionaryMission Trajectory Generator (EMTG). The paper also defines an empirical-basedprocess to characterize the maximum step size for the target arrival dates in theLambert grid search. Lastly, a candidate mission to two KBOs is presented. Theresults indicate that the ∆V computed from the STM propagations is not repre-sentative of the final ∆V computed in EMTG; however, it does serve as a useful‘reachability’ metric to identify nearby KBOs.

Miguel Benayas Penas↗
NASA NTRSDate not supplied

A Framework for Sense and Follow Convoys for Collective Autonomous Mobility

Convoys are collections of vehicles that share similar velocity profiles. In the sense-and follow convoy construct, a vehicle can follow a member of an existing convoy resulting in convoy chaining. We prove conditions under which this can occur such that the resulting convoy chain is bounded and the velocities of all members converge to the leader velocity through locally distributed control algorithms. To assess the approach, we utilize a six degree-of-freedom rigid body vehicle dynamics model for each agent. A dynamic inversion based control law is used to track the desired trajectory generated by the convoy algorithms. To simulate the system, we utilize Unity, a cross-platform game engine, where 3-dimensional terrain, building, and vehicle data can be visualized. Numerous simulations are presented to illustrate the concept.

convoys↗
NASA NTRSDate not supplied

A Framework for Sense and Follow Convoys for Collective Autonomous Mobility

Convoys are collections of vehicles that share similar velocity profiles. In the sense-and follow convoy construct, a vehicle can follow a member of an existing convoy resulting in convoy chaining. We prove conditions under which this can occur such that the resulting convoy chain is bounded and the velocities of all members converge to the leader velocity through locally distributed control algorithms. To assess the approach, we utilize a six degree-of-freedom rigid body vehicle dynamics model for each agent. A dynamic inversion based control law is used to track the desired trajectory generated by the convoy algorithms. To simulate the system, we utilize Unity, a cross-platform game engine, where 3-dimensional terrain, building, and vehicle data can be visualized. Numerous simulations are presented to illustrate the concept. Link to video file below:

convoys↗
NASA NTRSDate not supplied

SIRIUS: Simulation Infrastructure for Research on Interoperating Unmanned Systems

This paper presents the Simulation Infrastructure for Research on Interoperating Unmanned Systems (SIRIUS), a research framework for simulation and analysis of future conceptual Urban Air Mobility (UAM) operations. SIRIUS is being developed under the auspices of the NASA Air Traffic Management eXploration project, UAM subproject (ATM-X UAM). SIRIUS provides an intuitive, highly configurable graphical user interface to design complex traffic scenarios and airspace configurations representative of conceptual UAM operations. Aircraft simulated with SIRIUS can be equipped with flight-tested capabilities for detect and avoid (DAA), geofencing, distributed merging and spacing, path conformance, and path planning while executing time-constrained, 4D trajectories generated by a UAM ground operations system. Central to the design of the SIRIUS simulation framework is the capability to evaluate the integration and interoperability of ground-based separation services (e.g., strategic separation) with extended DAA functionality (e.g., path monitoring, separation provision, merging and spacing, etc.) The simulation environment also supports modelling of wind, navigation, and sensor uncertainties, as well as communication delays. SIRIUS enables distributed simulation of large-scale scenarios. An interactive graphical analysis capability helps isolate, visualize, and compare relevant vehicle state data and widely used measures of performance metrics across multiple scenarios.

Andrew Peters↗
NASA NTRSDate not supplied

Modeling Deformable Linear Objects for Autonomous Robotic Outfitting of Lunar Surface Systems

This paper presents structural models of deformable linear objects (DLOs). DLOs are a subclass of deformable objects that encompasses common outfitting elements such as cables and ropes. Models are validated through hardware experiments, and integration in a robotic autonomy architecture for space environments is discussed. A persistent human presence on the lunar surface is one of the next major milestones in space exploration. This requires the development of robust extraplanetary construction technologies including structures and materials modeling and robotic systems. Previous robotic construction technology development has primarily focused on structural assembly, with significantly less focus on robotically performed outfitting tasks to instantiate subsystems providing power, data, life support, etc. These tasks involve manipulation of highly flexible elements, which are difficult to model, such as cable harnesses, ropes, and hoses. Robotic manipulation of DLOs, especially cable harnesses, is an active area of research as cable harnesses are essential for providing power and data to space assets. DLO models that can be used for robot manipulator trajectory generation are necessary for autonomous operation of lunar infrastructure. There are many proposed methods for modeling DLOs, and they primarily fall into three types: 1) discrete model-based, 2) continuum model-based, and 3) Neural Network-based. These types each have pros and cons, and the tradeoff between model accuracy and computational speed informs which type should be used. An understanding of this trade-off is imperative for real-time control of autonomous systems. High computational requirements reduce the speed of the model, making real-time control difficult, while accuracy is critical to preventing collisions. Discrete models, such as a mass-spring multibody representation, require relatively few calculations, and accuracy is directly tied to the step size of the discretization. Continuum models, such as a B-spline representation or a Cosserat rod model (a mix of continuous and discrete), are more informed of the structural properties of the cable and are much more accurate than a rigid body mass-spring model, but at significant computational cost. A Neural Network approach can provide an online solution with very few computational steps, but properly generating training data can be difficult and validation for an in-space application is not trivial. This paper explores the trade-off between different modeling approaches and compares accuracy and computational speed/complexity of the three types mentioned above. Model accuracy is evaluated using a cable in a static configuration. True cable shape is obtained using a depth camera for RGB images and point-cloud segmentation. The purpose of this experiment is to evaluate the trade-offs of different approaches to the DLO modeling problem. Understanding the tradeoffs between different cable modeling techniques paves the way for developing robotic control and planning architectures necessary for real-time manipulation of DLOs for lunar infrastructure outfitting. Real-time control is required for robotic systems to be able to actively manipulate a cable in a harsh environment where model and sensor errors compound, and environmental conditions can cause significant disturbances. Cable routing must be performed in areas with high density of objects/obstacles: through truss structures, near solar panels or mirror arrays, next to bundles of electrical equipment. Understanding the best way to plan and manipulate a cable without disrupting the environment or damaging the cable is imperative to robotic outfitting operations on the lunar surface.

Amy M Quartaro↗
NASA NTRSDate not supplied

Successive Convexification for Powered Descent Guidance with Time-Varying Mass Properties

This paper extends the 6 degree-of-freedom successive convexification (SCvx) algorithm discussed in literature to account for time-varying mass properties in the representation of the attitude dynamics. Simulation results of a notional large-size lander performing the last minutes of Lunar powered descent with significant variations in the center-of-mass and moments of inertia over the duration of the trajectory are shown. Differences in the final optimal trajectories generated via SCvx are presented between the constant vs. variable mass property formulations for an in-plane and out-of-plane example.

Alex Hayes↗
NASA NTRSDate not supplied

Successive Convexification for Powered Descent Guidance with Time-Varying Mass Properties

This paper extends the 6 degree-of-freedom successive convexification (SCvx) algorithm discussed in literature to account for time-varying mass properties in the representation of the attitude dynamics. Simulation results of a notional large-size lander performing the last minutes of Lunar powered descent with significant variations in the center-of-mass and moments of inertia over the duration of the trajectory are shown. Differences in the final optimal trajectories generated via SCvx are presented between the constant vs. variable mass property formulations for an in-plane and out-of-plane example.

Alex Hayes↗
NASA NTRS1972

Generation of NEP heliocentric trajectory data

A study, designed to generate representative nuclear electric propulsion data for rendezvous missions to the comet Encke using the variational calculus program HILTOP, is presented. Other purposes of the study include a comparison of the HILTOP data with equivalent data generated with QUICKTOP program and to propose approaches for storing and subsequently accessing the optimum trajectory and performance data in the QUICKLY program.

Horsewood, J. L.↗