EP3598417A1 - Verfahren zur flugbahnplanung unbemannter luftfahrzeuge unter verwendung von flugrouten von vögeln - Google Patents

Verfahren zur flugbahnplanung unbemannter luftfahrzeuge unter verwendung von flugrouten von vögeln Download PDF

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Publication number
EP3598417A1
EP3598417A1 EP18183957.2A EP18183957A EP3598417A1 EP 3598417 A1 EP3598417 A1 EP 3598417A1 EP 18183957 A EP18183957 A EP 18183957A EP 3598417 A1 EP3598417 A1 EP 3598417A1
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EP
European Patent Office
Prior art keywords
data
flight path
birds
flight
recording
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Granted
Application number
EP18183957.2A
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English (en)
French (fr)
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EP3598417B1 (de
Inventor
Shu-Hui Kao
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Min Xin Technology Corp
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Min Xin Technology Corp
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0004—Transmission of traffic-related information to or from an aircraft
    • G08G5/0013—Transmission of traffic-related information to or from an aircraft with a ground station
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0017—Arrangements for implementing traffic-related aircraft activities, e.g. arrangements for generating, displaying, acquiring or managing traffic information
    • G08G5/0026—Arrangements for implementing traffic-related aircraft activities, e.g. arrangements for generating, displaying, acquiring or managing traffic information located on the ground
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/003—Flight plan management
    • G08G5/0034—Assembly of a flight plan
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0043—Traffic management of multiple aircrafts from the ground
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0047—Navigation or guidance aids for a single aircraft
    • G08G5/0069—Navigation or guidance aids for a single aircraft specially adapted for an unmanned aircraft
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft, e.g. air-traffic control [ATC]
    • G08G5/0073—Surveillance aids
    • G08G5/0086—Surveillance aids for monitoring terrain

Definitions

  • the present invention relates to a method for flight path planning and, more particularly, to a method using racing pigeons that carry recording devices to fly, planning optimal flight paths through calculation using data associated with acquired flight paths, and inputting the optimal flight paths to an unmanned aerial vehicles (UAVs) for the UAVs to fly according to the optimal flight paths.
  • UAVs unmanned aerial vehicles
  • UAVs have become more and more widespread.
  • the high mobility of UAVs is the key point to make them widely acceptable.
  • an UAV equipped with a camera or video recorder can fly to places that are inaccessible to monitor natural disasters, such as earthquake, volcano eruption, flood or land slide, or to urban areas to keep track of traffic flow, road structure inspection and construction overview of public facilities, so as to acquire sufficient accurate information.
  • shooting aerial photography of an area in a wide-range fashion facilitates awareness of the changing trend of the area good for policy setting.
  • UAVs can be used to ship merchandise in another example.
  • the UAVs used to deliver merchandise can avoid streets with traffic jam and directly fly to the designated destination for delivery without being stopped by traffic lights and stop signs, thus providing a time-saving measure for merchandise delivery especially in a long-range delivery.
  • UAVs To avoid obstruction in the flight, generally, users manually operate the UAVs.
  • users can control the UAVs to make a turn to avoid the obstruction by operating a controller such as a rocker stick.
  • the constraint of such control means resides in a limited distance for connectivity between the UAVs and the controller.
  • the UAVs When located beyond the limited distance, the UAVs either fail to continuously fly any more or collide with obstructions due to failure of obstruction identification.
  • users In consideration of continuous control over the UAVs, users must be located within a maximum connection range with the UAVs. In other words, the criteria for users to keep moving based on movement of the UAVs, which is inconvenient to users, should be met. Meanwhile, line of sight between users and UAVs should be met. Supposing that light of sight between UAVs and users fails to be maintained, even if the UAVs are located within a controllable range, users are still unable to determine the flying direction of the UAVs.
  • a second method avoiding obstruction is to directly fly to a space above high-rise buildings after departure of the UAVs, such that the UAVs can fly to a space above the destination along a straight line and then descend vertically to effectively avoid obstructions located between buildings.
  • the vertical ascending height of the UAVs should increase as well, not only costing more energy but taking more time to fly to the destination. Meanwhile, UAVs encountering unstable air flow in a high-altitude environment are crash-prone.
  • a third method of flight path planning for UAVs is to install all kinds of environmental sensors on the UAVs, such as infrared (IR) sensors, ultrasonic sensors, lidar (Light Detection and Ranging), and/or camera lens and perform an obstruction-avoiding algorithm.
  • IR infrared
  • ultrasonic sensors ultrasonic sensors
  • lidar Light Detection and Ranging
  • camera lens performs an obstruction-avoiding algorithm.
  • IR infrared
  • lidar Light Detection and Ranging
  • camera lens perform an obstruction-avoiding algorithm
  • An objective of the present invention is to provide a method for flight path planning of unmanned aerial vehicles (UAVs) using flying routes of birds, which employs multiple recording devices respectively installed on multiple racing pigeons to record flying tracks of the racing pigeons between two places, utilizes an analyzing device to identify a most effective and obstruction-free flight path, and inputs the flight path to a UAV for the UAV to effectively and safely fly between the two places.
  • UAVs unmanned aerial vehicles
  • the method of flight path planning of UAVs using flying routes of birds includes steps of:
  • the present invention adopts the animal instinct of racing pigeons that automatically avoids obstruction during flight to create multiple flying tracks between two places, and selects one most appropriate flying track as the flight path of the UAV.
  • the flying distance or the flying time should be the minimum. Accordingly, the UAV can not only fly without the concern of colliding with obstruction but rapidly arrive at the destination to attain the goal of saving time and cost of consumed energy.
  • a method of flight path planning of unmanned aerial vehicles using flying routes of birds in accordance with the present invention includes the following steps.
  • Step S 101 Record multiple pieces of flight data.
  • multiple recording devices 10 are respectively installed on multiple birds, which may be racing pigeons. Given racing pigeons as an example, the multiple racing pigeons are released from a first designated point and predefine a second designated point as a destination.
  • each recording device 10 is an electronic foot ring and may configure a fixed time period therein beforehand, which may be 2 seconds or 5 seconds or is adjustable based on users' demands.
  • the recording devices record one piece of flight data once every the fixed time period in generation of the multiple pieces of flight data, which record latitude, longitude, height, UTC (Coordinated Universal Time), flight direction and flight speed of the racing pigeon at a present location.
  • Step S102 Generate an optimal flight path.
  • the optimal flight path is generated as follows.
  • Step S211 Generate multiple flying tracks.
  • the racing pigeon will carry one recording device 10 and fly from the first designated point to the second designated point.
  • the recording device 10 records one piece of flight data every the fixed time period at a data-recording point and outputs the piece of flight data to an analyzing device 20.
  • the analyzing device 20 connects all the data-recording points and groups all the pieces of flight data to generate the flying tracks.
  • the analyzing devices 20 can generate at least one flying track from the respective pieces of flight data.
  • Step S212 Select an optimal one of the multiple flying tracks as the optimal flight path.
  • the analyzing device 20 selects one of the flying tracks of the racing pigeons with the shortest flying time as the optimal flight path.
  • the analyzing device 20 selects one of the flying tracks of the racing pigeons with the shortest flying distance as the optimal flight path.
  • Another way of establishing the at least one optimal flight path is as follows.
  • Step S221 Acquire multiple pieces of optimal flight data.
  • the analyzing device 20 calculates a shortest distance between the first designated point and the second designated point, connects the first designated point and the second designated point with the shortest distance as a shortest path, and selects the pieces of flight data closest to the shortest path as the multiple pieces of optimal flight data.
  • Step S222 Acquire the optimal flight path.
  • the multiple pieces of optimal flight data are grouped to form the optimal flight path.
  • Step S103 Control a UAV 30 to fly according to the optimal flight path.
  • the optimal flight path is acquired from Step S102 and is inputted into the UAV 30 for the UAV 30 to fly between the first designated point and the second designated point according to the optimal flight path.
  • FIG. 3 Under the circumstance of a large-range flying distance, with reference to Fig. 3 , an actual flying track for the racing pigeons to fly from the first designated point SP to the second designated point FP is shown. Before departure of a racing pigeon, the fixed time period is preset to be 15 seconds. With reference to Fig. 4A , as shown in the pieces of flight data, when the racing pigeon carrying the recording device 10 flies to a first data-recording point DP1, the recording device 10 records a first piece of flight data DATA1 at the first data-recording point DP1, and a recording time and a height of the first piece of flight data DATA1 are 6'59"09 and 9 meters respectively.
  • the racing pigeon flies to a second data-recording point DP2 15 seconds later.
  • the recording device 10 records a second piece of flight data DATA2 at the second data-recording point DP2, and the recording time and the height of the second piece of flight data DATA2 are 6'59"24 and 8 meters respectively.
  • the racing pigeon is in a non-flying state.
  • the recording device 10 when the racing pigeon flies to a twenty-ninth data-recording point DP29, the recording device 10 also records a twenty-ninth piece of flight data at the twenty-ninth data-recording point DP29.
  • the recording time, a distance from the departure point, the height, and a speed associated with the twenty-ninth data-recording point DP29 are 42'26, 18.97 kilometers, 42 meters and 734.41 meters/minute respectively.
  • the recording device 10 also records a thirtieth piece of flight data at the thirtieth data-recording point DP30.
  • the recording time, a distance from the departure point, the height, and a speed associated with the thirtieth data-recording point DP30 are 45'26, 23.23 kilometers, 53 meters and 1419.62 meters/minute respectively.
  • the analyzing device 20 can group data associated with all data-recording points to constitute a first flying track TRACK1.
  • the analyzing device 20 After analyzing all the pieces of flight data associated with all data-recording points at the first flying track TRACK1, the analyzing device 20 outputs a first flight speed curve 31 and a first flight height curve 32 and calculates multiple pieces of advanced data.
  • Each piece of advanced data includes an average flight speed, a maximum flight speed per hour, an average flight height, and the like.
  • the multiple pieces of flight data recorded by the recording device 10 carried by each different racing pigeon are grouped by the analyzing device 20 to generate multiple flying tracks respectively.
  • there are three flying tracks namely a first flying track TRACK1, a second flying track TRACK2, and a third flying track TRACK3.
  • the second flying track TRACK2 and the third flying track TRACK3 are superimposed on one another, so it can tell that all the flying tracks TRACK1, TRACK2, TRACK3 differ to a certain extent.
  • the flying track with a shortest flying distance is taken as an optimal flight path.
  • the first flying track TRACK1 has the shortest flying distance
  • all the pieces of flight data associated with the first flying track TRACK1 are inputted to the UAV for the UAV to fly according to the optimal flight path.
  • each racing pigeon carrying the recording device 10 flies from the first designated point SP to the second designated point FP in an urban area, and the recording device 10 records the piece of flight data at each data-recording point, such as a fifty-fifth piece of flight data DATA55 at a fifty-fifth data-recording point DP55.
  • the analyzing device 20 outputs multiple pieces of second flight data to a trending diagram.
  • the trending diagram includes a second flight height curve 41 and a second flight speed curve 42 associated with the multiple pieces of second flight data.
  • the feature of automatically avoiding obstruction during flight of racing pigeons allow large amount of racing pigeons carrying the recording devices 10 to fly from the first designated point SP to the second designated point FP for acquisition of an optimal flight path, such that the optimal flight path can be inputted into a UAV for the UAV to fly according to the optimal flight path, not only significantly lowering the chance of colliding with obstruction during flight but saving time and cost of energy consumption because of shortened flying time and distance.
  • racing pigeons carrying the respective recording devices 10 are allowed to fly between two different points in an area.
  • those data-recording points recorded by the recording device 10 are also locations to which UAVs can fly to and can be grouped to create an obstruction-free airspace in the area, which includes all the data-recording points safely accessible to all the racing pigeons.
  • the analyzing device 20 can be used to pick all the data-recording points that form the shortest path between the first designated point SP to the second designated point FP and then input those data-recording points to the UAVs for the UAVs to safely and rapidly fly from the first designated point SP to the second designated point FP, ensuring that the UAVs are not damaged due to collision with obstruction during the flight.
  • timely update of flight path planning and safe airspace can be performed based on seasonal and environmental variation to ensure that flight safety and performance of UAVs can be secured and the effect of economical energy can be achieved.

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  • Engineering & Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Traffic Control Systems (AREA)
  • Navigation (AREA)
EP18183957.2A 2018-07-17 2018-07-17 Verfahren zur flugbahnplanung unbemannter luftfahrzeuge unter verwendung von flugrouten von vögeln Active EP3598417B1 (de)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP18183957.2A EP3598417B1 (de) 2018-07-17 2018-07-17 Verfahren zur flugbahnplanung unbemannter luftfahrzeuge unter verwendung von flugrouten von vögeln

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Application Number Priority Date Filing Date Title
EP18183957.2A EP3598417B1 (de) 2018-07-17 2018-07-17 Verfahren zur flugbahnplanung unbemannter luftfahrzeuge unter verwendung von flugrouten von vögeln

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EP3598417A1 true EP3598417A1 (de) 2020-01-22
EP3598417B1 EP3598417B1 (de) 2020-09-09

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE29701049U1 (de) * 1997-01-22 1997-03-13 Göcke, Wilhelm, Dipl.-Ing., 48341 Altenberge Einrichtung als virtuelle Brieftaubenrennbahn zur Beobachtung von Preisflügen von Brieftauben
WO2009054721A1 (en) * 2007-10-23 2009-04-30 Sightflight Europe B.V. Tracking system for moving objects, usually animals, mainly migratory birds and in particular carrier pigeons
US9262929B1 (en) * 2014-05-10 2016-02-16 Google Inc. Ground-sensitive trajectory generation for UAVs

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE29701049U1 (de) * 1997-01-22 1997-03-13 Göcke, Wilhelm, Dipl.-Ing., 48341 Altenberge Einrichtung als virtuelle Brieftaubenrennbahn zur Beobachtung von Preisflügen von Brieftauben
WO2009054721A1 (en) * 2007-10-23 2009-04-30 Sightflight Europe B.V. Tracking system for moving objects, usually animals, mainly migratory birds and in particular carrier pigeons
US9262929B1 (en) * 2014-05-10 2016-02-16 Google Inc. Ground-sensitive trajectory generation for UAVs

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
HAIBIN DUAN ET AL: "Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning", INTERNATIONAL JOURNAL OF INTELLIGENT COMPUTING AND CYBERNETICS, vol. 7, no. 1, 4 March 2014 (2014-03-04), pages 24 - 37, XP055533117, ISSN: 1756-378X, DOI: 10.1108/IJICC-02-2014-0005 *

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