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At least 19 records

Region based route planning - Multi-abstraction route planning based on intermediate level vision processing

Intermediate and high level processing operations are performed on vision data for the organization of images into more meaningful, higher-level topological representations by means of a region-based route planner (RBRP). The RBRP operates in terrain scenarios where some or most of the terrain is occluded, proceeding without a priori maps on the basis of two-dimensional representations and gradient-and-roughness information. Route planning is accomplished by three successive abstractions and yields a detailed point-by-point path by searching only within the boundaries of relatively small regions.

Doshi, Rajkumar S.↗

Route planning in a four-dimensional environment

Robots must be able to function in the real world. The real world involves processes and agents that move independently of the actions of the robot, sometimes in an unpredictable manner. A real-time integrated route planning and spatial representation system for planning routes through dynamic domains is presented. The system will find the safest most efficient route through space-time as described by a set of user defined evaluation functions. Because the route planning algorthims is highly parallel and can run on an SIMD machine in O(p) time (p is the length of a path), the system will find real-time paths through unpredictable domains when used in an incremental mode. Spatial representation, an SIMD algorithm for route planning in a dynamic domain, and results from an implementation on a traditional computer architecture are discussed.

Slack, M. G.↗

SPRINT: Scheduling Planning Routing Intersatellite Network Tool

The Scheduling Planning Routing Intersatellite Network Tool (SPRINT) software system plans and schedules the operations (observations, inter-satellite crosslink communications, and ground communications) of Earth observation (EO) constellations of hundreds of resource-constrained small satellites to enable global, near real-time science. Historically, most CubeSats have flown radios only for direct-to-ground downlink of data; as a result, data availability is delayed by as long as it takes for the capturing satellite to pass over a ground station, typically hours. Current Planning and Scheduling (P&S) systems for constellations cannot handle data routing through a large, dynamic network topology, and all planning is handled on the ground without .the ability to autonomously prioritize important observations, or respond to unexpected changes in communication window or bandwidth. SPRINT directly handles both data routing for low latency bulk observation data downlink and replanning onboard to deal with dynamic priorities and fault response, maximizing the utility of downlinked data.

Kerri Cahoy↗

A Practical Approach to Obstacle Field Route Planning for Unmanned Rotorcraft

Autonomous helicopter operations in the near-earth environment will require robust and efficient obstacle field route planning. A method for obstacle field route planning is presented, which is composed of a mesh generation phase, a graph search phase, and a route refinement phase. The method mixes optimization and heuristics to obtain a satisfactory solution quickly. Simulations based on an unmanned helicopter model are presented.

Howlet, Jason K.↗

Application of fuel/time minimization techniques to route planning and trajectory optimization

Rising fuel costs combined with other economic pressures have resulted in industry requirements for more efficient air traffic control and airborne operations. NASA has responded with an on-going research program to investigate the requirements and benefits of using new airborne guidance and pilot procedures that are compatible with advanced air traffic control systems and that will result in more fuel efficient flight. The results of flight testing an airborne computer algorithm designed to provide either open-loop or closed-loop guidance for fuel efficient descents while satisfying time constraints imposed by the air traffic control system is summarized. Some of the potential cost and fuel savings that are obtained with sophisticated vertical path optimization capabilities are described.

Knox, C. E.↗

Improved Results for Route Planning in Stochastic Transportation Networks

In the bus network problem, the goal is to generate a plan for getting from point X to point Y within a city using buses in the smallest expected time. Because bus arrival times are not determined by a fixed schedule but instead may be random. the problem requires more than standard shortest path techniques. In recent work, Datar and Ranade provide algorithms in the case where bus arrivals are assumed to be independent and exponentially distributed. We offer solutions to two important generalizations of the problem, answering open questions posed by Datar and Ranade. First, we provide a polynomial time algorithm for a much wider class of arrival distributions, namely those with increasing failure rate. This class includes not only exponential distributions but also uniform, normal, and gamma distributions. Second, in the case where bus arrival times are independent and geometric discrete random variable,. we provide an algorithm for transportation networks of buses and trains, where trains run according to a fixed schedule.

Boyan, Justin↗

Interfaces For Planning Vehicle Routes

A system for producing vehicle routes such as aircraft flight plans in the presence of weather and other hazards defines static and moving hazards with polygons drawn on a display containing graphic hazard regions. Different hazard types and intensities are displayed differently. Both lateral and vertical geographic depictions are displayed, and hazards can be displayed temporally as well. Users input information and thresholds for hazards.

Thea Lynn Feyereisen↗

Delay Banking for Managing Air Traffic

Delay banking has been invented to enhance air-traffic management in a way that would increase the degree of fairness in assigning arrival, departure, and en-route delays and trajectory deviations to aircraft impacted by congestion in the national airspace system. In delay banking, an aircraft operator (airline, military, general aviation, etc.) would be assigned a numerical credit when any of their flights are delayed because of an air-traffic flow restriction. The operator could subsequently bid against other operators competing for access to congested airspace to utilize part or all of its accumulated credit. Operators utilize credits to obtain higher priority for the same flight, or other flights operating at the same time, or later, in the same airspace, or elsewhere. Operators could also trade delay credits, according to market rules that would be determined by stakeholders in the national airspace system. Delay banking would be administered by an independent third party who would use delay banking automation to continually monitor flights, allocate delay credits, maintain accounts of delay credits for participating airlines, mediate bidding and the consumption of credits of winning bidders, analyze potential transfers of credits within and between operators, implement accepted transfers, and ensure fair treatment of all participating operators. A flow restriction can manifest itself in the form of a delay in assigned takeoff time, a reduction in assigned airspeed, a change in the position for the aircraft in a queue of all aircraft in a common stream of traffic (e.g., similar route), a change in the planned altitude profile for an aircraft, or change in the planned route for the aircraft. Flow restrictions are typically imposed to mitigate traffic congestion at an airport or in a region of airspace, particularly congestion due to inclement weather, or the unavailability of a runway or region of airspace. A delay credit would be allocated to an operator of a flight that has accepted, or upon which was imposed, a flow restriction. The amount of the credit would increase with the amount of delay caused by the flow restriction, the exact amount depending on which of several candidate formulas is eventually chosen. For example, according to one formula, there would be no credit for a delay smaller than some threshold value (e.g., 30 seconds) and the amount of the credit for a longer delay would be set at the amount of the delay minus the threshold value. Optionally, the value of a delay credit could be made to decay with time according to a suitable formula (e.g., an exponential decay). Also, optionally, a transaction charge could be assessed against the value of a delay credit that an operator used on a flight different from the one for which the delay originated or that was traded with a different operator. The delay credits accumulated by a given airline could be utilized in various ways. For example, an operator could enter a bid for priority handling in a new flow restriction that impacts one or more of the operator s flights; if the bid were unsuccessful, all or a portion of the credit would be returned to the bidder. If the bid pertained to a single aircraft that was in a queue, delay credits could be consumed in moving the aircraft to an earlier position within the queue. In the case of a flow restriction involving a choice of alternate routes, planned altitude profile, aircraft spacing, or other non-queue flow restrictions, delay credits could be used to bid for an alternative assignment.

Green, Steve↗

Method and apparatus for identification of hazards along an intended travel route

Targets proximate to a travel route plan were evaluated to determine hazardousness. Projected geometric representation of a vehicle determines intrusion of hazardous targets along travel route plan. Geometric representation of hazardous targets projected along motion vector to determine intrusion upon travel route plan. Intrusion assessment presented on user display.

Kronfeld, Kevin M.↗

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support en-route flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Layton, Charles↗

Unmanned Aerial Systems Traffic Management (UTM): Safely Enabling UAS Operations in Low-Altitude Airspace

Currently, there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS flight operations. Given this, and understanding that the FAA faces a mandate to modernize the present air traffic management system through computer automation and significantly reduce the number of air traffic controllers by FY 2020, the FAA maintains that a comprehensive, yet fully automated UAS traffic management (UTM) system for low-altitude airspace is needed. The concept of UTM is to begin by leveraging concepts from the system of roads, lanes, stop signs, rules and lights that govern vehicles on the ground today. Building on its legacy of work in air traffic management (ATM), NASA is working with industry to develop prototype technologies for a UAS Traffic Management (UTM) system that would evolve airspace integration procedures for enabling safe, efficient low-altitude flight operations that autonomously manage UAS operating in an approved low-altitude airspace environment. UTM is a cloud-based system that will autonomously manage all traffic at low altitudes to include UASs being operated beyond visual line of sight of an operator. UTM would thus enable safe and efficient flight operations by providing fully integrated traffic management services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning re-routing, separation management, sequencing spacing, and contingency management. UTM removes the need for human operators to continuously monitor aircraft operating in approved areas. NASA envisions concepts for two types of UTM systems. The first would be a small portable system, which could be moved between geographical areas in support of operations such as precision agriculture and public safety. The second would be a Persistent system, which would support low-altitude operations in an approved area by providing continuous automated coverage. Both would require persistent communication, navigation, and surveillance (CNS) coverage to track, ensure, and monitor conformance. UTM is creating an airspace management tool that allows the ATM system to accommodate the number of UAS that will operate in the low altitude airspace. The analogy is just because we have a car, whether its autonomous or someone is driving, does not diminish the need for a road or road signs or rules of the road.

traffic management↗

A workstation-based evaluation of a far-field route planner for helicopters

Helicopter flight missions at very low, nap of the Earth, altitudes place a heavy workload on the pilot. To aid in reducing this workload, Ames Research Center has been investigating various types of automated route planners. As part of an automated preflight mission planner, a route planner algorithm aids in selecting the overall (far-field) route to be flown. During the mission, the route planner can be used to replan a new route in case of unexpected threats or change in mission requirements. An evaluation of a candidate route planning algorithm, based on dynamic programming techniques is described. This algorithm meets most of the requirements for route planning, both preflight and during the mission. In general, the requirements are to minimize the distance and/or fuel and the deviation from a flight time schedule, and must be flyable within the constraints of available fuel and time.

Warner, David N., Jr.↗

Route Generation for a Synthetic Character (BOT) Using a Partial or Incomplete Knowledge Route Generation Algorithm in UT2004 Virtual Environment

This paper presents a new Route Generation Algorithm that accurately and realistically represents human route planning and navigation for Military Operations in Urban Terrain (MOUT). The accuracy of this algorithm in representing human behavior is measured using the Unreal Tournament(Trademark) 2004 (UT2004) Game Engine to provide the simulation environment in which the differences between the routes taken by the human player and those of a Synthetic Agent (BOT) executing the A-star algorithm and the new Route Generation Algorithm can be compared. The new Route Generation Algorithm computes the BOT route based on partial or incomplete knowledge received from the UT2004 game engine during game play. To allow BOT navigation to occur continuously throughout the game play with incomplete knowledge of the terrain, a spatial network model of the UT2004 MOUT terrain is captured and stored in an Oracle 11 9 Spatial Data Object (SOO). The SOO allows a partial data query to be executed to generate continuous route updates based on the terrain knowledge, and stored dynamic BOT, Player and environmental parameters returned by the query. The partial data query permits the dynamic adjustment of the planned routes by the Route Generation Algorithm based on the current state of the environment during a simulation. The dynamic nature of this algorithm more accurately allows the BOT to mimic the routes taken by the human executing under the same conditions thereby improving the realism of the BOT in a MOUT simulation environment.

Hanold, Gregg T.↗

Planning The Route Of A Robotic Land Vehicle

Algorithm enables experimental robotic land vehicle to follow automatically route computed on basis of terrain-height-map data. Computer executing algorithm merges coarser global topographical data with finer local topographical data obtained through stereoscopic video system as vehicle moves along, then smoothes merged elevation map, interpolates map to evenly-horizontally-spaced grid points, and differentiates map to produce data on slopes and roughness for use in calculations of traversability and optimum route(s). Distance traveled minimized to extent possible consistent with avoidance of obstacles.

Gennery, Donald B.↗

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support enroute flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Layton, Charles↗

Unmanned Aircraft Systems Traffic Management (UTM) Safely Enabling UAS Operations in Low-Altitude Airspace

Unmanned Aircraft System (UAS) Traffic Management (UTM) Enabling Civilian Low-Altitude Airspace and Unmanned Aircraft System Operations What is the problem? Many beneficial civilian applications of UAS have been proposed, from goods delivery and infrastructure surveillance, to search and rescue, and agricultural monitoring. Currently, there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS operations, regardless of the type of UAS. A UAS traffic management (UTM) system for low-altitude airspace may be needed, perhaps leveraging concepts from the system of roads, lanes, stop signs, rules and lights that govern vehicles on the ground today, whether the vehicles are driven by humans or are automated. What system technologies is NASA exploring? Building on its legacy of work in air traffic management for crewed aircraft, NASA is researching prototype technologies for a UAS Traffic Management (UTM) system that could develop airspace integration requirements for enabling safe, efficient low-altitude operations. While incorporating lessons learned from the today's well-established air traffic management system, which was a response that grew out of a mid-air collision over the Grand Canyon in the early days of commercial aviation, the UTM system would enable safe and efficient low-altitude airspace operations by providing services such as airspace design, corridors, dynamic geofencing, severe weather and wind avoidance, congestion management, terrain avoidance, route planning and re-routing, separation management, sequencing and spacing, and contingency management. One of the attributes of the UTM system is that it would not require human operators to monitor every vehicle continuously. The system could provide to human managers the data to make strategic decisions related to initiation, continuation, and termination of airspace operations. This approach would ensure that only authenticated UAS could operate in the airspace. In its most mature form, the UTM system could be developed using autonomicity characteristics that include self-configuration, self-optimization and self-protection. The self-configuration aspect could determine whether the operations should continue given the current andor predicted windweather conditions. NASA envisions concepts for two types of possible UTM systems. The first type would be a Portable UTM system, which would move from between geographical areas and support operations such as precision agriculture and disaster relief. The second type of system would be a Persistent UTM system, which would support low-altitude operations and provide continuous coverage for a geographical area. Either system would require persistent communication, navigation, and surveillance (CNS) coverage to track, ensure, and monitor conformance. What is NASA doing to test the technologies? NASA's near-term goal is the development and demonstration of a possible future UTM system that could safely enable low-altitude airspace and UAS operations. Working alongside many committed government, industry and academic partners, NASA is leading the research, development and testing that is taking place in a series of activities called Technology Capability Levels (TCL), each increasing in complexity. UTM TCL1 concluded field testing in August 2015 and is undergoing additional testing at an FAA site.

UTM Low-altitude↗