Search NASA⌕ Search

SEARCH · Search NASA

Results for “Collision Avoidance”

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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

NASA UAS Integration into the NAS Project: Human Systems Integration

This presentation provides an overview of the work the Human Systems Integration (HSI) sub-project has done on detect and avoid (DAA) displays while working on the UAS (Unmanned Aircraft System) Integration into the NAS project. The most recent simulation on DAA interoperability with Traffic Collision Avoidance System (TCAS) is discussed in the most detail. The relationship of the work to the larger UAS community and next steps are also detailed.

unmanned aircraft systems↗
NASA NTRS1992

Robot path planning for space-truss assembly

Construction, repair, and maintenance of space-based structures will require extensive planning of operations in order to effectively carry out these tasks. The path planning algorithm described here is a general approach to generating paths that guarantee collision avoidance for a single chain nonredundant or redundant robot. The algorithm uses a graph search of feasible points in position space, followed by a local potential field method that guarantees collision avoidance among objects, structures, and the robot arm as well as conformance to joint limit constraints. This algorithm is novel in its computation of goal attractive potential fields in Cartesian space, and computation of obstacle repulsive fields in robot joint space. These effects are combined to generate robot motion. Computation is efficiently implemented through the computation of the robot arm Jacobian and not the full inverse arm kinematics. These planning algorithms have been implemented and evaluated using existing space-truss designs, and are being integrated into the RPI-CIRSSE Testbed environment.

Muenger, Rolf↗
NASA NTRS1988

Collision detection for planning collision-free motion of two robot arms

The authors focus on collision detection for planning collision-free motion of two robot arms in a common workspace. A collision-free motion is obtained by detecting collisions along the straight-line trajectories of the robots using a sphere model for the wrists and then replanning the paths and/or trajectories of one or both of the robots to avoid collisions. A novel approach to collision detection is presented and a discussion on collision avoidance is given.

Basta, Robert A.↗
NASA NTRSDate not supplied

Ground to Air Testing of a Fused Optical-Radar Aircraft Detection and Tracking System

Onboard detection and tracking capability are integral to the sensing component in collision avoidance systems needed to safely operate autonomous urban air taxis and small Unmanned Aircraft Systems. Ground-based validation of detection and tracking systems is an important milestone towards the end goal of real-time collision avoidance using onboard sensors and algorithms. In this work, we evaluate three Extended Kalman Filter(EKF)based fusion trackers with radar and vision detection inputs, and compare them with baseline trackers for each sensor type. Performance is assessed using field collected data of ground to air test flights with the sensors co-located on a stable platform with an instrumented multirotor acting as the intruder performing a waypoint pattern at a distance of1.1km to 0.3km to simulate a head-on collision geometry. Fusing an image-based morphological detector with a radar detector using an EKF covered 74% of the ground truth position updates logged by the flight controller on the multirotor within 50 meters after accounting for alignment offsets while covering 15% more ground truth updates relative to radar only. Removing timestamps when the intruder aircraft is occluded by trees and only considering timestamps where the radar has an update, the EKF image-based morphological detector combined with the radar detector covered 90% of the of the ground truth position updates within 50metersand 97% within 100 meters.

Chester V Dolph↗
NASA NTRSDate not supplied

Aerial Object Trajectory Classification by Training on Flight Controller Data and Testing on RADAR Generated Tracks

Onboard collision avoidance is needed to enable safe, autonomous flight operations for NASA projects such as Advanced Air Mobility (AAM), as well as many commercial applications. Real-time aerial object classification will improve onboard collision avoidance algorithm decision making and may reduce unnecessary activation of avoidance systems. This work trains an aircraft trajectory classifier using trajectories from flight controller logs and tests the classifier using RADAR collected trajectories during air to air experiments and ground to air experiments. In contrast to RADAR data, these flight controller logs are relatively abundant, which makes the possibility of substituting flight data for RADAR data an attractive, cost-effective option. The SVM model developed in this work achieved a 79.7% classification accuracy on the first second of radar trajectories of GA, multirotor sUAS, and fixed wing sUAS. Findings from this work indicate that it is feasible to classify sensor collected trajectories using a classifier trained on flight controller data.

Henry Holbrook↗
NASA NTRS2022

DataSet: Aerial Object Trajectory Classification by Training on Flight Controller Data and Testing on RADAR Generated

Onboard collision avoidance is needed to enable safe, autonomous flight operations for NASA projects such as Advanced Air Mobility (AAM), as well as many commercial applications. Real-time aerial object classification will improve onboard collision avoidance algorithm decision making and may reduce unnecessary activation of avoidance systems. This work trains an aircraft trajectory classifier using trajectories from flight controller logs and tests the classifier using RADAR collected trajectories during air to air experiments and ground to air experiments. In contrast to RADAR data, these flight controller logs are relatively abundant, which makes the possibility of substituting flight data for RADAR data an attractive, cost-effective option. The SVM model developed in this work achieved a 79.7% classification accuracy on the first second of radar trajectories of GA, multirotor sUAS, and fixed wing sUAS. Findings from this e that it is feasible to classify sensor collected trajectories using a classifier trained flight controller data.

Chester V Dolph↗
NASA NTRS2016

UAS in the NAS Flight Test Series 4 Overview

Flight Test Series 4 (FT4) provides the researchers with an opportunity to expand on the data collected during the first flight tests. Following Flight Test Series 3, additional scripted encounters with different aircraft performance and sensors will be conducted. FT4 is presently planned for Spring of 2016 to ensure collection of data to support the validation of the final RTCA Phase 1 DAA (Detect and Avoid) Minimum Operational Performance Standards (MOPS). There are three research objectives associated with this goal: Evaluate the performance of the DAA system against cooperative and non-cooperative aircraft encounters Evaluate UAS (Unmanned Aircraft Systems) pilot performance in response to DAA maneuver guidance and alerting with live intruder encounters Evaluate TCAS/DAA (Traffic Alert and Collision Avoidance System/Detect and Avoid) interoperability. This flight test series will focus on only the Scripted Encounters configuration, supporting the collection of data to validate the interoperability of DAA and collision avoidance algorithms.

flight test↗
NASA NTRS1995

Issues in Airborne Systems for Closely-Spaced Parallel Runway Operations

Efforts to increase airport capacity include studies of aircraft systems that would enable simultaneous approaches to closely spaced parallel runways in Instrument Meteorological Conditions (IMC). The time-critical nature of a parallel approach results in key design issues for current and future collision avoidance systems. These issues are being studied in two ways. First, a part-task flight simulator study has examined the procedural and display issues inherent in such a time-critical task. Second, a prototype collision avoidance logic capable of generating this maneuver guidance has been designed using a recently developed methodology.

Pritchett, A.↗
NASA NTRS2016

A Numerical Approach to Estimate the Ballistic Coefficient of Space Debris from TLE Orbital Data

Low Earth Orbit (LEO) is full of space debris, which consist of spent rocket stages, old satellites and fragments from explosions and collisions. As of 2009, more than 21,000 orbital debris larger than 10 cm are known to exist], and while it is hard to track anything smaller than that, the estimated population of particles between 1 and 10 cm in diameter is approximately 500,000, whereas small as 1 cm exceeds 100 million. These objects orbit Earth with huge kinetic energies speeds usually exceed 7 kms. The shape of their orbit varies from almost circular to highly elliptical and covers all LEO, a region in space between 160 and 2,000 km above sea level. Unfortunately, LEO is also the place where most of our active satellites are situated, as well as, International Space Station (ISS) and Hubble Space Telescope, whose orbits are around 400 and 550 km above sea level, respectively.This poses a real threat as debris can collide with satellites and deal substantial damage or even destroy them.Collisions between two or more debris create clouds of smaller debris, which are harder to track and increase overall object density and collision probability. At some point, the debris density couldthen reach a critical value, which would start a chain reaction and the number of space debris would grow exponentially. This phenomenon was first described by Kessler in 1978 and he concluded that it would lead to creation of debris belt, which would vastly complicate satellite operations in LEO. The debris density is already relatively high, as seen from several necessary debris avoidance maneuvers done by Shuttle, before it was discontinued, and ISS. But not all satellites have a propulsion system to avoid collision, hence different methods need to be applied. One of the proposed collision avoidance concepts is called LightForce and it suggests using photon pressure to induce small orbital corrections to deflect debris from colliding. This method is very efficient as seen from theoretical simulations, even few continuous mode 10 kW ground-based lasers, focused by 1.5 m telescopes with adaptive optics, were enough to prevent significant amount of the debris collisions. Simulations were done by propagating all space objects in LEO by 1 year into the future and checking whether the probability of collision was high. For those space objects different ground-based lasers were used to divert them, afterwards collision probabilities were reevaluated. However, the actual accuracy of the LightForce software, which has been developed at NASA AmesResearch Center, depends on the veracity of the input parameters, one of which is the objects ballistic coefficient. It is a measure of bodys ability to overcome air resistance, which has a significant impact on the debris in LEO, and thus it is responsible for the shape of the trajectory of the debris. Having the exact values of the ballistic coefficient would make significantly better collision predictions, unfortunately, we do not know what are the values for most of the objects.In this research, we were working with part of LightForce code, which estimates the ballistic coefficient from ephemerides. Previously used method gave highly inaccurate values, when compared to known objects, and it needed to be changed. The goal of this work was to try out a different method of estimating the ballistic coefficient and to check whether or not it gives noticeable improvements.

Collisions↗
NASA NTRS1997

Pilot Non-Conformance to Alerting System Commands During Closely Spaced Parallel Approaches

Cockpit alerting systems monitor potentially hazardous situations, both inside and outside the aircraft. When a hazard is projected to occur, the alerting system displays alerts and/or command decisions to the pilot. However, pilots have been observed to not conform to alerting system commands by delaying their response or by not following the automatic commands exactly. This non-conformance to the automatic alerting system can reduce its benefit. Therefore, a need exists to understand the causes and effects of pilot non-conformance in order to develop automatic alerting systems whose commands the pilots are more likely to follow. These considerations were examined through flight simulator evaluations of the collision avoidance task during closely spaced parallel approaches. This task provided a useful case-study because the effects of non-conformance can be significant, given the time-critical nature of the task. A preliminary evaluation of alerting systems identified non-conformance in over 40% of the cases and a corresponding drop in collision avoidance performance. A follow-on experiment found subjects' alerting and maneuver selection criteria were consistent with different strategies than those used by automatic systems, indicating the pilot may potentially disagree with the alerting system if the pilot attempts to verify automatic alerts and commanded avoidance maneuvers. A final experiment found supporting automatic alerts with the explicit display of its underlying criteria resulted in more consistent subject reactions. In light of these experimental results, a general discussion of pilot non-conformance is provided. Contributing factors in pilot non-conformance include a lack of confidence in the automatic system and mismatches between the alerting system's commands and the pilots' own decisions based on the information available to them. The effects of non-conformance on system performance are discussed. Possible methods of reconciling mismatches are given, and design considerations for alerting systems which alleviate the problem of non-conformance are provided.

Pritchett, Amy Ruth↗
NASA NTRS2015

Recommended Screening Practices for Launch Collision Aviodance

The objective of this document is to assess the value of launch collision avoidance (COLA) practices and provide recommendations regarding its implementation for NASA robotic missions. The scope of this effort is limited to launch COLA screens against catalog objects that are either spacecraft or debris. No modifications to manned safety COLA practices are considered in this effort. An assessment of the value of launch COLA can be broken down into two fundamental questions: 1) Does collision during launch represent a significant risk to either the payload being launched or the space environment? 2) Can launch collision mitigation be performed in a manner that provides meaningful risk reduction at an acceptable level of operational impact? While it has been possible to piece together partial answers to these questions for some time, the first attempt to comprehensively address them is documented in reference (a), Launch COLA Operations: an Examination of Data Products, Procedures, and Thresholds, Revision A. This report is the product of an extensive study that addressed fundamental technical questions surrounding launch collision avoidance analysis and practice. The results provided in reference (a) will be cited throughout this document as these two questions are addressed. The premise of this assessment is that in order to conclude that launch COLA is a value-added activity, the answer to both of these questions must be affirmative. A "no" answer to either of these questions points toward the conclusion that launch COLA provides little or no risk mitigation benefit. The remainder of this assessment will focus on addressing these two questions.

recommended screening practicies luanch collision ↗
NASA NTRS2017

Gaussian Mixture Models for Temporal Depth Fusion

Sensing the 3D environment of a moving robot is essential for collision avoidance. Most 3D sensors produce dense depth maps, which are subject to imperfections due to various environmental factors. Temporal fusion of depth maps is crucial to overcome those. Temporal fusion is traditionally done in 3D space with voxel data structures, but it can be approached by temporal fusion in image space, with potential benefits in reduced memory and computational cost for applications like reactive collision avoidance for micro air vehicles. In this paper, we present an efficient Gaussian Mixture Models based depth map fusion approach, introducing an online update scheme for dense representations. The environment is modeled from an ego-centric point of view, where each pixel is represented by a mixture of Gaussian inverse-depth models. Consecutive frames are related to each other by transformations obtained from visual odometry. This approach achieves better accuracy than alternative image space depth map fusion techniques at lower computational cost.

Matthies, Larry↗
NASA NTRS1995

Collision management utilizing CCD and remote sensing technology

With the threat of damage to aerospace systems (space station, shuttle, hypersonic a/c, solar power satellites, loss of life, etc.) from collision with debris (manmade/artificial), there exists an opportunity for the design of a novel system (collision avoidance) to be incorporated into the overall design. While incorporating techniques from ccd and remote sensing technologies, an integrated system utilized in the infrared/visible spectrum for detection, tracking, localization, and maneuvering from doppler shift measurements is achievable. Other analysis such as impact assessment, station keeping, chemical, and optical tracking/fire control solutions are possible through this system. Utilizing modified field programmable gated arrays (software reconfiguring the hardware) the mission and mission effectiveness can be varied. This paper outlines the theoretical operation of a prototype system as it applies to collision avoidance (to be followed up by research).

Mcdaniel, Harvey E., Jr.↗
NASA NTRS1996

A Virtual Audio Guidance and Alert System for Commercial Aircraft Operations

Our work in virtual reality systems at NASA Ames Research Center includes the area of aurally-guided visual search, using specially-designed audio cues and spatial audio processing (also known as virtual or "3-D audio") techniques (Begault, 1994). Previous studies at Ames had revealed that use of 3-D audio for Traffic Collision Avoidance System (TCAS) advisories significantly reduced head-down time, compared to a head-down map display (0.5 sec advantage) or no display at all (2.2 sec advantage) (Begault, 1993, 1995; Begault & Pittman, 1994; see Wenzel, 1994, for an audio demo). Since the crew must keep their head up and looking out the window as much as possible when taxiing under low-visibility conditions, and the potential for "blunder" is increased under such conditions, it was sensible to evaluate the audio spatial cueing for a prototype audio ground collision avoidance warning (GCAW) system, and a 3-D audio guidance system. Results were favorable for GCAW, but not for the audio guidance system.

Begault, Durand R.↗
NASA NTRS2011

Asset Analysis and Operational Concepts for Separation Assurance Flight Testing at Dryden Flight Research Center

A preliminary survey of existing separation assurance and collision avoidance advancements, technologies, and efforts has been conducted in order to develop a concept of operations for flight testing autonomous separation assurance at Dryden Flight Research Center. This effort was part of the Unmanned Aerial Systems in the National Airspace System project. The survey focused primarily on separation assurance projects validated through flight testing (including lessons learned), however current forays into the field were also examined. Comparisons between current Dryden flight and range assets were conducted using House of Quality matrices in order to allow project management to make determinations regarding asset utilization for future flight tests. This was conducted in order to establish a body of knowledge of the current collision avoidance landscape, and thus focus Dryden s efforts more effectively towards the providing of assets and test ranges for future flight testing within this research field.

Costa, Guillermo J.↗
NASA NTRS2012

A Geometric Analysis to Protect Manned Assets from Newly Launched Objects - COLA Gap Analysis

A safety risk was identified for the International Space Station (ISS) by The Aerospace Corporation following the launch of GPS IIR-20 (March 24, 2009), when the spent upper stage of the launch vehicle unexpectedly crossed inside the ISS notification box shortly after launch. This event highlighted a 56-hour vulnerability period following the end of the launch Collision Avoidance (COLA) process where the ISS would be unable to react to a conjunction with a newly launched object. Current launch COLA processes screen each launched object across the launch window to determine if an object's nominal trajectory is predicted to pass within 200 km of the ISS (or any other manned/mannable object), resulting in a launch time closure. These launch COLA screens are performed from launch through separation plus I 00 minutes. Once the objects are in orbit, they are cataloged and evaluated as part of routine on-orbit conjunction assessment processes. However, as the GPS IIR-20 scenario illustrated, there is a vulnerability period in the time line between the end of launch COLA coverage and the beginning of standard on-orbit COLA assessment activities. The gap between existing launch and on-orbit COLA processes is driven by the time it takes to track and catalog a launched object, identify a conjunction, and plan and execute a collision avoidance maneuver. For the ISS, the total time required to accomplish an of these steps is 56 hours. To protect human lives, NASA/JSC has requested that an US launches take additional steps to protect the ISS during this "COLA gap" period. The uncertainty in the state of a spent upper stage can be quite large after all bums are complete and all remaining propellants are expelled to safe the stage. Simply extending the launch COLA process an additional 56 hours is not a viable option as the 3-sigma position uncertainty will far exceed the 200 km miss-distance criterion. Additionally, performing a probability of collision (Pc) analysis over this period is also not practical due to the limiting effects of these large orbit state uncertainties. An estimated upper bound for Pc for a typical spent upper stage if nominally aligned for a direct broadside collision with the ISS is only on the order of 10-6. For a smaller manned object such as a Soyuz capsule, the risk level decreases to an order of 10'8 . In comparison, the Air Force Range policy (AFI 91-217) for launch COLAs would only eliminate launch opportunities when conjunctions with objects exceed a Pc of 10'5 This paper demonstrates a conservative geometry-based methodology that may be used to determine if launch opportunities pose a threat to the ISS during the COLA gap period. The NASA Launch Services Program at Kennedy Space Center has developed this COLA gap analysis method and employed it fQr three NASA missions to identify potential ISS conjunctions and corresponding launch window closures during the 56-hour at-risk period. In the analysis, for each launch opportunity, the nominal trajectory of the spent upper stage and the orbit state of the ISS are propagated over the 56 hour period. Each time the upper stage crosses the orbit plane of the ISS, the relative radial and argument of latitude separations are calculated. A window cutout is identified if these separation differences fall within a mission-specific violation box, which is determined from the evaluation of a Monte Carlo dispersions analysis that quantifies the potential variation in the upper stage radial and argument of latitude differences. This paper details the results of these analyses and their impacts to each mission.

Hametz, Mark E.↗
NASA NTRS2017

Distributed Spatiotemporal Motion Planning for Spacecraft Swarms in Cluttered Environments

This paper focuses on trajectory planning for spacecraft swarms in cluttered environments, like debris fields or the asteroid belt. Our objective is to reconfigure the spacecraft swarm to a desired formation in a distributed manner while minimizing fuel and avoiding collisions among themselves and with the obstacles. In our prior work we proposed a novel distributed guidance algorithm for spacecraft swarms in static environments.1 In this paper, we present the Multi-Agent Moving-Obstacles Spherical Expansion and Sequential Convex Programming (MAMO SE–SCP) algorithm that extends our prior work to include spatiotemporal constraints such as time-varying, moving obstacles and desired time-varying terminal positions. In the MAMO SE–SCP algorithm, each agent uses a spherical-expansion-based sampling algorithm to cooperatively explore the time-varying environment, a distributed assignment algorithm to agree on the terminal position for each agent, and a sequential-convex-programming-based optimization step to compute the locally-optimal trajectories from the current location to the assigned time-varying terminal position while avoiding collision with other agent and the moving obstacles. Simulations results demonstrate that the proposed distributed algorithm can be used by a spacecraft swarm to achieve a time-varying, desired formation around an object of interest in a dynamic environment with many moving and tumbling obstacles.

Hadaegh, Fred Y.↗
NASA NTRS2017

Distributed Spatiotemporal Motion Planning for Spacecraft Swarms in Cluttered Environments

This paper focuses on trajectory planning for spacecraft swarms in cluttered environments, like debris fields or the asteroid belt. Our objective is to reconfigure the spacecraft swarm to a desired formation in a distributed manner while minimizing fuel and avoiding collisions among themselves and with obstacles. In our prior work we proposed a novel distributed guidance algorithm for spacecraft swarms in static environments. In this paper, we present the Multi-Agent Moving-Obstacles Spherical Expansion and Sequential Convex Programming (MAMO SE-SCP) algorithm that extends our prior work to include spatiotemporal constraints such as time-varying, moving obstacles and desired time-varying terminal positions. In the MAMO SE-SCP algorithm, each agent uses a spherical-expansion-based sampling algorithm to cooperatively explore the time-varying environment, a distributed assignment algorithm to agree on the terminal position for each agent, and a sequential-convex-programming-based optimization step to compute the locally-optimal trajectories from the current location to the assigned time-varying terminal position while avoiding collision with other agents and moving obstacles. Simulation results demonstrate that the proposed distributed algorithm can be used by a spacecraft swarm to achieve a time-varying, desired formation around an object of interest in a dynamic environment with many moving and tumbling obstacles.

Bandyopadhyay, Saptarshi↗