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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

A Multi-Modality Mobility Concept for a Small Package Delivery UAV

This paper will discuss a different approach to the typical notional small package delivery drone concept. Most delivery drone concepts employ a point-to-point aerial delivery CONOPS (Concept of Operations) from a warehouse directly to the front or back yards of a customers residence or a commercial office space. Instead, the proposed approach is somewhat analogous to current postal deliveries: a small aerial vehicle flies from a warehouse to designated neighborhood VTOL (Vertical Take-Off and Landing) landing spots where the aerial vehicle then converts to a "roadable" (ground-mobility) vehicle that then transits on sidewalks and/or bicycle paths till it arrives to the residence/office drop-off points. This concept and associated platform or vehicle will be referred in this paper as MICHAEL (Multimodal Intra-City Hauling and Aerial-Effected Logistics) concept. It is suggested that the MICHAEL concept potentially results in a more community friendly "delivery drone" approach.

UAV↗
NASA NTRSDate not supplied

Rolling Horizon with K-Position Search Method for Strategic Deconfliction of Package Delivery UAS

In this research, the strategic deconfliction of unmanned aircraft systems for an urban package delivery environment with two depots and multiple drop-off locations is studied. This research aims to formulate a mathematical model to compute both the departure sequence and scheduled time of departure for each unmanned aircraft system at a depot, considering temporal constraints at en-route crossing waypoints and depots for strategic deconfliction. However, the problem formulation results in an NP-hard mixed-integer nonlinear programming problem for the global optimal solution, so instead, a "rolling horizon with𝑘-position search"heuristic method is developed. The simulation studies show that an increase in the value of𝑘(the parameter used to determine the size of the local neighborhood) reduces the average ground delay at the cost of an increase in the computation time for a given problem size. The study also shows an order of magnitude increase in the maximum number of flights scheduled with the integration of rolling horizon (time decomposition) compared to those without the integration of rolling horizon in the heuristic algorithm for a given computation time cut off.

UTM↗
NASA NTRSDate not supplied

Rolling Horizon with K-Position Search Method for Strategic Deconfliction of Package Delivery UAS

This research focuses on the strategic deconfliction of unmanned aircraft systems (UAS) in an urban package delivery environment with two depots and multiple drop-off locations. Since the formulated mixed-integer nonlinear programming (MINLP) problem is non-deterministic polynomial-time (NP) hard, a heuristic algorithm called "rolling horizon with k-position search (KPS)" is used to compute the departure sequence and scheduled time of departure (STD) of each UAS at a depot, considering temporal constraints at en-route crossing waypoints and depots for strategic deconfliction. The simulation studies show that an increase in the value of k (local neighborhood search) in the KPS reduces the average ground delay at the cost of an increase in the computation time for a given number of UAS, size of the rolling horizon window, and number of depots involved in the local neighborhood search. The studies also show that for a given rolling horizon window, the computation time increases exponentially with an increase in the total number of UAS flights when serial processing the local neighborhood search of KPS (with k > 1) and drops by an order of magnitude upon performing the local neighborhood search of KPS using parallel processing instead of serial processing. The computation time drops with the reduction in air traffic complexity of a scenario for a given number of flights, k (local neighborhood search), and rolling horizon window.

UTM↗
DOE OSTI2025

Packaged delivery of CRISPR–Cas9 ribonucleoproteins accelerates genome editing

Effective genome editing requires a sufficient dose of CRISPR–Cas9 ribonucleoproteins (RNPs) to enter the target cell while minimizing immune responses, off-target editing, and cytotoxicity. Clinical use of Cas9 RNPs currently entails electroporation into cells ex vivo, but no systematic comparison of this method to packaged RNP delivery has been made. Here we compared two delivery strategies, electroporation and enveloped delivery vehicles (EDVs), to investigate the Cas9 dosage requirements for genome editing. Using fluorescence correlation spectroscopy, we determined that >1300 Cas9 RNPs per nucleus are typically required for productive genome editing. EDV-mediated editing was >30-fold more efficient than electroporation, and editing occurs at least 2-fold faster for EDV delivery at comparable total Cas9 RNP doses. We hypothesize that differences in efficacy between these methods result in part from the increased duration of RNP nuclear residence resulting from EDV delivery. Our results directly compare RNP delivery strategies, showing that packaged delivery could dramatically reduce the amount of CRISPR–Cas9 RNPs required for experimental or clinical genome editing.

60 APPLIED LIFE SCIENCES↗
NASA NTRSDate not supplied

Traffic Flow Analysis for Package Delivery Drones using a Queueing Model

A key component of the small unmanned aircraft systems traffic management ecosystem is the design of scalable algorithms for strategic deconfliction of drones prior to takeoff. In this work, we focus on efficient flow management of drones on a network of intersecting edges subject to two kinds of spacing constraints: 1) between any two adjacent vehicles on an edge and 2) between any two vehicles on two different edges arriving one after the other at an intersection. The spacing is designed to enable non-intersection of operational volumes corresponding to two different vehicles thereby properly separating the vehicles inside each volume. For simplicity, we assume a constant ground speed for the drones and fixed dimensions for the operational volume blocks. The deconfliction is managed by adjusting the takeoff time of the drones, thereby regulating their arrival time at various crossing waypoints in the network. This framework allows us to study the maximum flow (throughput) of vehicles on a network of edges connecting depots to drop off sites subject to the temporal spacing constraints. The departure scheduling of individual drones results in a combinatorial optimization problem. To alleviate this, we solve a max-flow formulation and use queueing theory to simplify the analysis and provide upper bounds to the underlying optimization problem for individual drone departure scheduling. Our results indicate that throughput drops rapidly after the density of drones in the network passes the max-flow limits.

Alexey A Munishkin↗
NASA NTRSDate not supplied

Aerial Vehicle Routing and Scheduling for UAS Traffic Management: A Monte Carlo Tree Search Approach

Numerous unmanned aircraft systems operating at low altitudes to deliver goods and services may one day become ubiquitous in our cities. In the Unmanned Aircraft Systems (UAS) Traffic Management (UTM) framework, such a concept is envisioned, where aerial vehicles operate beyond visual line of sight (BVLOS) within specifically reserved and time stamped “corridors” in the airspace. For example, these corridors or operational intent volumes can connect an aerial vehicle’s origin site to its destination site for package delivery operations. There may also be more than one corridor available for an aerial vehicle to choose from and often different corridors may intersect with one another. Thus, it is imperative to ensure flight trajectories belonging to different aerial vehicles are not in conflict. Per the UTM CONOPs, we assume that a vehicle almost always stays inside its corridor or operational volume. This work provides a framework for strategic deconfliction of UTM or package delivery drones, where we schedule the departure time of all vehicles subject to various temporal constraints (including the corridor deconfliction at the intersections). We present the “multi-route weighted package delivery problem” which serves as an exemplifying model for strategic deconfliction in UTM. In the multi-route weighted package delivery problem, a graph network is given which consists of a set of depots (source) and drop-off (destination) nodes, with multiple routes (defined as a sequence of waypoints) connecting the depots to drop-off nodes. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is for a known set of aerial vehicles to depart from the depots, choose a route and take off time, while avoiding conflicts with other aerial vehicles, and minimizing both risk and distance traveled. We provide a mixed integer linear programming (MILP) formulation of the problem, as well as a heuristic solution based on Monte Carlo Tree Search (MCTS) – a method used in game theory and artificial intelligence – to overcome limitations inherent to optimal solvers. Computational results show the advantages of using MCTS over the MILP formulation; the former can provide a sub-optimal solution quickly, and may sometimes even reach an optimal solution, whereas the latter may not even produce a solution in reasonable time. Furthermore, results from both the MILP formulation and MCTS methods were validated using a preliminary agent-based simulator implementing the UTM concept of operations. Thus, the MCTS method can be seen as a scalable solution to the complex multi-route weighted package delivery problem and may possibly be extended to similar complex optimization problems.

Kenny Chour↗
NASA NTRSDate not supplied

Usability of an Updated Version of the Supplemental Data Service Provider-Consolidated Dashboard for Supporting Uncrewed Aircraft System Traffic Management

The Supplemental Data Service Provider-Consolidated Dashboard (SDSP-CD) is a preflight planning user interface (UI) that serves to aid operators when drafting routes for small uncrewed aircraft systems (sUASs). The primary function of the SDSP-CD is to identify hazards that an sUAS may encounter along a proposed flight path and assess the severity of these risks. A usability study was conducted on an updated version of the SDSP-CD to determine if the most recent iterations made to the system improved objective performance and subjective user experience. There are two main components of the SDSP-CD interface: (1) the dashboard and (2) the interactive map. The dashboard provides users with hazard and vehicle limitations for each sUAS in their fleet while the map contains a graphical representation of each vehicle’s route, hazard details, and geographic information. A series of preflight risk-assessment questions and tasks were developed to examine how participants interact with the updated version of the SDSP-CD. Additionally, a new service that measures vertiport congestion was developed and included as one of the services that was tested. In the present study, participants were trained to use the SDSP-CD and then completed two simulated scenarios during which they performed a variety of tasks, responded to questions, and completed surveys. The two scenarios developed for the present study were the Package Delivery and Hurricane Preparation scenarios. The Package Delivery scenario involved a fleet of four sUASs delivering low-stakes items (e.g., lunches and snacks) to people in a fictitious city. The Hurricane Preparation scenario involved a fleet of 11 sUASs delivering a range of supplies (from medicine to boardgames) to employees stranded at an office park due to road closures caused by an impending hurricane. Participants assumed the role of a fleet manager during both scenarios and were responsible for managing the sUASs in their fleet. Questions included those with objectively correct responses, open-ended strategy responses, and subjective user experience feedback. It was found that participants were largely successful at using the SDSP-CD interface to answer questions with objectively correct responses. Additionally, participants were able to use reasoning and logic based on the information available in the SDSP-CD to determine the cause of various risks and what actions they would consider taking. Finally, although participants reported that there were elements of the UI that could be improved, overall feedback pertaining to user experience suggested that the SDSP-CD concept is viable.

usability testing↗
NASA NTRSDate not supplied

Operator Workload and Task Allocation in m:N Operational Architectures of Uncrewed Aerial Systems

Uncrewed aerial systems (UAS) show promise in urban air transport, package delivery, and emergency services. UAS efficiency can be significantly improved by having fewer operators (m) manage a greater number of vehicles (N), or the m:N architecture of operation. The current study investigates how workload affects operators’ task-allocation decision-making and potential effects of two crucial human factors: trust and self-confidence. In the context of a simulated UAS package-delivery task, 10 participants with expertise in UAS operation were recruited. Each participant reported their preferred task-allocation strategy for a set of five subtasks while watching two sets of videos with different workload levels. Perceived workload, trust, and self-confidence were also measured after each video session. Overall, participants indicated a preference for automation for most of the subtasks under the delivery mission. Trust, rather than workload and self-confidence, played a significant role in experts’ decisions of task-allocation and assignment methods. Higher trust led to higher preference for automation.

workload↗
NASA NTRSDate not supplied

Aerial Vehicle Routing and Scheduling for UAS Traffic Management: A Hybrid Monte Carlo Tree Search Approach

We present the Multi-Route Weighted Package Delivery Problem (MRWPDP) and a scalable solution methodology as a major step towards enabling an airspace deconfliction service for drone delivery operations. The problem is motivated by Strategic deconfliction under the FAA’s “Unmanned Aircraft Systems Traffic Management” Concept of Operations. MRWPDP falls under a class of vehicle routing and scheduling problems, and as such is NP-Hard. In MRWPDP, a graph network is given which consists of depots, drop-off sites, and multiple routes connecting the two. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is to optimally schedule the departure time and assign routes to a known set of vehicles at the depot. We propose a heuristic solution to the problem by borrowing techniques from Mixed Integer Linear Programming (MILP), Constraint Programming, and Monte Carlo Tree Search (MCTS). The resulting hybrid framework is MCTS with Bound-and-Prune (BP) and rapid simulated updates (U), or MCTS-BP-U. This approach is able to quickly provide a feasible solution for MRWPDP, even for large problem instances up to 1000 vehicles. We provide a MILP formulation of MRWPDP and compare its performance against MCTS-BP-U in terms of solution quality. An agent-based model simulation is conducted as a final step to validate the efficacy of our approach.

air traffic scheduling↗
NASA NTRSDate not supplied

Aerial Vehicle Routing and Scheduling for UAS Traffic Management: A Hybrid Monte Carlo Tree Search Approach

We present the Multi-Route Weighted Package Delivery Problem (MRWPDP) and a scalable solution methodology as a major step towards enabling an airspace deconfliction service for drone delivery operations. The problem is motivated by Strategic deconfliction under the FAA’s “Unmanned Aircraft Systems Traffic Management” Concept of Operations. MRWPDP falls under a class of vehicle routing and scheduling problems, and as such is NP-Hard. In MRWPDP, a graph network is given which consists of depots, drop-off sites, and multiple routes connecting the two. In addition, routes are weighted by the associated ground risk and total travel distance for package delivery. The goal is to optimally schedule the departure time and assign routes to a known set of vehicles at the depot. We propose a heuristic solution to the problem by borrowing techniques from Mixed Integer Linear Programming (MILP), Constraint Programming, and Monte Carlo Tree Search (MCTS). The resulting hybrid framework is MCTS with Bound-and-Prune (BP) and rapid simulated updates (U), or MCTS-BP-U. This approach is able to quickly provide a feasible solution for MRWPDP, even for large problem instances up to 1000 vehicles. We provide a MILP formulation of MRWPDP and compare its performance against MCTS-BP-U in terms of solution quality. An agent-based model simulation is conducted as a final step to validate the efficacy of our approach.

air traffic scheduling↗
NASA NTRSDate not supplied

Automated Management of Small Unmanned Aircraft System Communications and Navigation Contingency

The number of small Unmanned Aircraft System (sUAS) operating in the low-altitude of the National Airspace System (NAS) has been rapidly increasing in the past few years and this number is expected to grow in the future. However, aside from a few special cases, all sUAS must fly within visual line-of-sight (VLOS) of their operators and this limitation is blocking highly anticipated beyond visual line-of-sight (BVLOS) sUAS applications such as package delivery from practice. To enable routine low-altitude BVLOS operations, there needs to be a traffic management ecosystem that complements the FAA’s Air Traffic Management (ATM) system, which does not provide air traffic services under 400 feet above ground level (AGL). NASA has been pioneering research and development of this ecosystem under UAS Traffic Management (UTM) project since 2015 in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting, and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for BVLOS operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 is building on the earlier TCLs and focuses on technologies and requirements for operations in higher-density urban areas for tasks such as newsgathering and package delivery and for managing large-scale contingencies. To coordinate and facilitate the incremental implementation of the UTM ecosystem in the NAS, a Research Transition Team (RTT) has been formed between the FAA, NASA, and industry. The RTT is divided into four subgroups, concept and use case development, data exchange and information architecture, sense and avoid, and communications and navigation (C&N). This paper focuses on C&N subgroup activities, in particular about the development of automated sUAS communications and navigation contingency management. The goal of this development is to prepare sUAS to display predictable behavior while handling C&N off-nominal events. It is expected that the adoption of the presented automated contingency management by the sUAS community will accommodate and inform rulemaking towards governing low-altitude BVLOS operations.

Unmanned Aviation System (UAS) Traffic Management↗
NASA NTRSDate not supplied

Automated Management of Small Unmanned Aircraft System (UAS) Communications and Navigation Contingency

The number of small Unmanned Aircraft System (sUAS) operating in the low-altitude of the National Airspace System (NAS) has been rapidly increasing in the past few years and this number is expected to grow in the future. However, aside from a few special cases, all sUAS must fly within visual line-of-sight (VLOS) of their operators and this limitation is blocking highly anticipated beyond visual line-of-sight (BVLOS) sUAS applications such as package delivery from practice. To enable routine low-altitude BVLOS operations, there needs to be a traffic management ecosystem that complements the FAA’s Air Traffic Management (ATM) system, which does not provide air traffic services under 400 feet above ground level (AGL). NASA has been pioneering research and development of this ecosystem under UAS Traffic Management (UTM) project since 2015 in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting, and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for BVLOS operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 is building on the earlier TCLs and focuses on technologies and requirements for operations in higher-density urban areas for tasks such as newsgathering and package delivery and for managing large-scale contingencies. To coordinate and facilitate the incremental implementation of the UTM ecosystem in the NAS, a Research Transition Team (RTT) has been formed between the FAA, NASA, and industry. The RTT is divided into four subgroups, concept and use case development, data exchange and information architecture, sense and avoid, and communications and navigation (C&N). This paper focuses on C&N subgroup activities, in particular about the development of automated sUAS communications and navigation contingency management. The goal of this development is to prepare sUAS to display predictable behavior while handling C&N off-nominal events. It is expected that the adoption of the presented automated contingency management by the sUAS community will accommodate and inform rulemaking towards governing low-altitude BVLOS operations.

Unmanned Aviation Systems (UAS) Traffic Management↗
NASA NTRS2017

External Contamination Environment at ISS Included: Selected Results from Payloads Contamination Mapping Delivery 3 Package

The International Space Station is the largest and most complex on-orbit platform for space science utilization in low Earth orbit. Multiple sites for external payloads, with exposure to the associated natural and induced environments, are available to support a variety of space science utilization objectives. Contamination is one of the induced environments that can impact performance, mission success and science utilization on the vehicle. The ISS has been designed, built and integrated with strict contamination requirements to provide low levels of induced contamination on external payload assets.

Olsen, Randy↗
NASA NTRS2016

Future Trends in Logistics and Sustainment

Airship Industry Study: In 2015, NASA Ames Research Center completed a study of the overall airship industry. The project called for a report that describes airship concepts proposed or projects initiated in recent years, airship performance or capability targets, and the missions these activities were addressing. The resulting report details the principal technical features of these airships, the proposed value/advantages of the features, notional concepts of operation, and challenges associated with such vehicles. The study investigated the current status and near-term prospects of these airship development activities, whether they are active or, if curtailed, the circumstances and possible reasons for that conclusion, including technical, business, or other mitigating factors. This presentation provides highlights of the Airship Industry Study investigations, findings, and recommendations. UAS Carrier Concept: The advantages of utilizing an airship as an airborne carrier for support and deployment of Unmanned Aircraft Systems (UAS) are examined. Whether as a stand-alone platform or in concert with conventional aircraft, the airship UAS carrier provides a number of compelling benefits for both military and civilian missions. As a mobile base it can remain operational despite political fallout that may render ground or ocean based UAS sites unavailable. It offers the psychological impact of a power projection tool that has few geographical limits, and holds promise as a new method for cost-saving intelligence gathering. It is also adaptable for civilian variants for supporting: emergency response, security/surveillance, delivery of medical/food supplies, as well as commercial package delivery to metropolitan and remote communities.

Hochstetler, Ron↗
NASA NTRS2016

Lighter-Than-Air (LTA) "AirStation": Unmanned Aircraft System (UAS) Carrier Concept

The advantages of utilizing an airship as an airborne carrier for support and deployment of Unmanned Aircraft Systems (UAS) are examined. Whether as a stand-alone platform or in concert with conventional aircraft, the airship UAS carrier provides a number of compelling benefits for both military and civilian missions. As a mobile base it can remain operational despite political fallout that may render ground or ocean based UAS sites unavailable. It offers the psychological impact of a power projection tool that has few geographical limits, and holds promise as a new method for cost-saving intelligence gathering. It is also adaptable for civilian variants for supporting: emergency response, security/surveillance, delivery of medical/food supplies, as well as commercial package delivery to metropolitan and remote communities. This paper presents the background on airship-aircraft operations, and explores the general airship carrier concept. Additionally, a catalog of contemporary technologies available to support the airship carrier concept are discussed, and essential elements for an Air-Station Development program proposed.

Hochstetler, Ronald D.↗
NASA NTRSDate not supplied

A Remote, Human-in-the-Loop Evaluation of a Multiple-Drone Delivery Operation

Over time, advances in unmanned aircraft systems (UAS) have enabled a shift in the operational paradigm from one operator managing one aircraft to that of multiple operators working together to manage multiple aircraft. This shift has highlighted the need for effective human-autonomy teaming methods to maintain manageable workload levels for operators as well as high standards of system performance and safety. This paper presents a study aimed at evaluating whether automation can help operators manage workload during small UAS (sUAS) package delivery scenarios featuring contingency situations. These contingency situations, resulting from unplanned UAS Volume Reservations (UVRs), required flight path reroutes for multiple aircraft simultaneously. The study manipulated the number of aircraft affected by the UVRs and the level of automation support. The presence of terrain conflicts was also controlled within each scenario. Due to the COVID-19 pandemic, subjects were not able to gain direct access to the Ground Control System (GCS). Therefore, the study was conducted using a subject-surrogate paradigm that required subjects to relay commands through a verbal protocol from remote locations outside of the lab to a researcher surrogate who had direct control of the GCS interfaces at the lab location. Results show that the automated support condition was associated with faster reroute response times, more efficient reroute maneuvers, and significantly lower levels of perceived workload than the manual reroute condition. However, the automation support level did not significantly impact pilots’ ability to avoid the UVR successfully; pilots were overwhelmingly capable of avoiding the UVR in all conditions. The presence of terrain conflicts primarily impacted pilot performance by leading to multiple uploads per vehicle, which was not typically required when pilots only needed to maneuver laterally. Although subjects did not have direct control over the GCS, subjective ratings indicate that the displays under test provided them with sufficient information to manage their aircraft and promptly respond to the unplanned UVRs. Overall, the objective and subjective data strongly suggest that the verbal protocol and subject-surrogate paradigm were effective methods for collecting data remotely amid the COVID-19 pandemic.

multi-UAS↗
NASA NTRS1992

Hermes CX-7: Air transport system design simulation

The Hermes CX-7 has been designed to service the overnight parcel package delivery needs of the cities of Aeroworld as determined in the G-Dome Enterprises market survey. The design optimization centers on the prime goal of servicing the needs of these cities as efficiently and profitably as possible. The greatest factors which affect the design of an aircraft for the mission outlined in the Request for Proposal are cost, construction feasibility and effectiveness of the design. Other influencing factors are given by the constraints of the market, including a maximum takeoff and landing distance of 60 feet, storage capability in a container of size 5 ft. x 3 ft. x 2 ft., cargo packages of 2 inch and 4 inch cubes, and ability to turn with a radius no larger than 60 feet. Safety considerations such as flying at or below Mach one (30 ft/s) and controllability and maintainability of the aircraft must also be designed into the aircraft. Another influential factor is the efficiency of the aircraft which involves optimizations and tradeoffs of such factors as weight, lifting surface sizing, structural redundancy, and material costs.

Amer, Brian↗