The present invention relates to Unmanned Aerial Vehicle (UAV) positioning system for repetitive UAV flights along a predefined flight path as well as a vehicle positioning kit. The UAV position system and the vehicle positioning kit may be used in particular for filming sport events particularly long-range sports such as skiing or motorsports as well as in movie productions. The UAV position system and vehicle positioning kit may also be used for surveillance or inspection of an environment where access to GPS is limited or unavailable. The invention also relates to a method for controlling the position of an UAV.
There are currently several tracking technologies available in the UAV industry among which the global positioning system (GPS) satellite-based system which uses a GPS receiver to receive location from the GPS satellites to determine the location of the UAV within a navigation environment. The GPS receiver periodically receives information from broadcasting GPS satellites and uses that information to triangulate the position of the UAV. However, in certain environments, GPS systems suffer from limited availability of the GPS signals and fail to work as well as may be desired.
Different positioning systems for UAV have been proposed to overcome the problem of sporadic loss of a GPS signal.
US2012/0197519 for example discloses a navigation system and method for determining a location of a navigator in a navigation environment using coded markers. The navigation system may include a camera apparatus configured to obtain an image of a scene containing images of at least one coded marker in a navigation environment, video analytics configured to read the at least one coded marker, and a processor coupled to the video analytics and configured to determine a position fix of a navigator based on a known location of the at least one coded marker.
In US2019/235531, systems and methods are provided for positioning an unmanned aerial vehicle-UAV in an environment. The UAV may be able to identify visual markers and patterns in the environment. The visual markers can be analyzed with visual sensors to determine the position of the UAV in the environment. The locating marker may be dynamic (e.g. changeable. Dynamic markers as disclosed in WO2016/065623 are in the form of a screen display (e.g. liquid crystals display (LCD), touch screen, LED screen, OLED screen, or plasma screen display) or projected on to a surface from a projector installed in the environment.
US2020/005656 describes a system for determining a location independent of a global navigation satellite system (GNSS) signal in autonomous vehicles, especially in UAVs. The system may comprise rigid strips comprising visual markers to guide the UAVs along a predefined path.
The above described markers have the inconvenient to be costly, difficult to set-up and/or to be changed to another set-up configuration.
An aim of the present invention is therefore to provide an Unmanned Aerial Vehicle (UAV) positioning system as well as a vehicle positioning kit that are easy and cost effective to set-up.
Another aim of the present invention is to provide an UAV positioning system, whereby a predetermined path of the position system can be easily modified according to the environment constraints.
A further aim of the present invention is to provide a method of controlling an UAV along a predefined path.
These aims are achieved, according to an aspect of the invention, by an Unmanned Aerial Vehicle (UAV) positioning system, comprising:
The position estimation module is configured to position the UAV above, below or next to the positioning stripe and therealong based on successive configurations of patterns captured by the camera of the position estimation module. The at least one positioning stripe comprises a controller configured to dynamically control active markers based on the velocity of the UAV and the positions of the active markers along the position stripe in order to generate the successive configurations of patterns.
In an embodiment, the UAV or the position estimation module further comprises an Inertial Measurement Unit (IMU).
In an embodiment, the active markers are arranged along the at least one positioning stripe at constant intervals.
In an embodiment, the markers are Light Emitted Diodes (LEDs).
In an embodiment, the LEDs are Near-IR LEDs, preferably in the spectral range from 920 nm to 960 nm, and most preferably around 940 nm.
In an embodiment, the at least one positioning stripe is made of several removably coupled segments in order to provide a length-adjustable positioning stripe.
In an embodiment, the at least one positioning stripe is flexible preferably made of a PVC base-material.
In an embodiment, the UAV positioning system comprises two flexible positioning stripes adapted to be arranged in parallel along said predefined path.
Another aspect of the invention relates to a method of controlling an Unmanned Aerial Vehicle (UAV) along a predefined path using a dynamically controlled positioning stripe, a position estimation module mounted the UAV and a control unit configured to control the velocity of the UAV. Active markers are distributed along the positioning stripe. Each marker is configured to be switched between an ON state and an OFF state to form different configurations of patterns. The position estimation module comprises a camera configured to captures images of portions of the positioning stripe.
The method comprises the steps of:
In an embodiment, the UAV is positioned above the positioning stripe at a certain height which is either controlled manually by the remote-control unit, or constant over and along the entire length of the positioning stripe or as a function of the x-y position of successive portions of the positioning stripe.
In an embodiment, the pose of the camera is fine-tuned based on information about yaw, pitch and roll angles sent to the UAV by the control unit.
In an embodiment, the UAV or the position estimation module comprises an Inertial Measurement Unit (IMU) (18). The pose of the camera is fine-tuned based on the measurements of the IMU.
In an embodiment, only the active markers of the positioning stripe in the vicinity of the UAV are controlled based on the image planes.
In an embodiment, the UAV or the position estimation module comprises a GPS sensor. A unique binary pattern is located near an end portion of the positioning stripe to send information to the UAV in order to switch from the positioning stripe to a GPS navigation system.
In an embodiment, the step of computing the ground truth position pi of the markers in terms of world coordinates [xiW, yiw, ziw] is achieved from a structure from motion (SFM) algorithm.
In an embodiment, the ego-motion of the camera is estimated using a non-linear estimator, for example an extended Kalman filter, in order to add temporal dependency between successive images captured by the camera and camera poses (C1, C2, C3).
Another aspect of the invention relates to a vehicle positioning kit, for example an Unmanned Aerial Vehicle (UAV), comprising:
The position estimation module is configured to position the vehicle above, below or next to the positioning stripe and therealong based on successive configurations of patterns captured by the camera of the position estimation module.
In an embodiment, the vehicle positioning kit further comprises a remote-control unit configured to control the velocity of the vehicle.
The invention will be better understood with the aid of the description of several embodiments given by way of examples and illustrated by the figures, in which:
As shown in
In an embodiment, active markers 32 are evenly distributed over the entire length of a dynamically controlled positioning stripe 30. The set of markers 32 may preferably be in the form of LEDs with a fixed inter-LED distance. By having real-time control over the LEDs 32, a unique binary pattern may be generated. Unique binary patterns allow the position estimation module 14 to recognize specific patterns formed by different group of LEDs 32 in order to locate itself relative to the flexible positioning stripe 30.
Specific pattern may also send additional information to the position estimation module 14 through decoding of the patterns. For example, a unique binary pattern may be located near one end portion of the dynamically controlled positioning stripe 30 to send information to the UAV in order to switch from the positioning stripe to another type of navigation system such as a GPS.
The light of each LED on the dynamically controlled positioning stripe 30 may be controlled based on its position on the stripe. If for example the LEDs at index positions 100-102 and 105-106 are turned on as shown in
The LEDs 32 may be attached for example to a PVC base-material which makes the positioning stripe 30 flexible and durable. The flexibility of the positioning stripe 30 enables to create curved drone trajectories and makes the handling during the setup very intuitive and easy. The positioning stripe 30 can also be attached to moving objects, walls, ceilings etc. The LEDs may advantageously be silicon coated, which makes the positioning stripe 30 waterproof for outdoor applications.
In an advantageous embodiment, the flexible positioning stripe 30 comprises near-field infrared LEDs emitting light at a wavelength ranging from 920 nm to 960 nm and preferably around 940 nm. Near-field infrared LEDs are advantageously not visible to the human eye while increasing the signal-to-noise ratio on the detection side. This makes the positioning stripe 30 particularly robust to outdoor applications.
According to this embodiment, the camera sensor 16 is an infrared sensor. For the efficient detection of the Near-field infrared LEDs 32, a band-pass filter in the same spectral frequency range is used in order to increase the signal-to-noise ratio drastically, which results in an image of mostly dark background with blobs of higher intensity corresponding to the LEDs as shown in
The camera comprises fisheye lens in order to increase the field of view for the detection of near-field infrared LEDs 32. This increases the possible dynamic range of the UAV 12 as well as the robustness of the position estimation itself. The camera sensor 16 may be of the type of a global shutter camera sensor to avoid distortions in the image when taken at high speed. The position estimation module 14 is configured to be powered directly by the UAV and includes a single-board computer
The (intensity weighted) centers of these bright blobs give the image coordinates of the corresponding LED 32. Each single LED is however not distinguishable from the others in the image plane. However, by detecting a group of markers, the underlying unique binary pattern the points belong to may be recognized. A single pattern entity may for example be recognized by a distinct preamble e.g. four subsequent LEDs 32 which are collectively turned on as shown in
With the additional knowledge of the fixed inter-LEDs distance d (
How the binary patterns are mapped onto the positioning stripe 30 is known according to the specific configuration of the positioning stripe. From recognizing a group of LEDs as a distinct pattern, the position of each single LED 32 relative to the positioning stripe 30 may be determined. Additionally, the ground truth position of each LED in terms of world coordinates [xiW, yiw, ziw] is computed with a preliminary mapping step. As a result, not only the position of each LED 32 along the positioning stripe 30 is known but also the actual spatial 3D information. From the set of LEDs positions, the shape of the positioning stripe 30 may be reconstructed with a spline interpolation.
With reference to
The variation of a structure from motion (SFM) algorithm makes the mapping more robust to the partially degenerate setting as shown in
In order to recover the full camera pose, the 2D coordinates zi of the detected LEDs in the image plane are matched to their corresponding LED indexes. Considering that the 3D world positions pi of each LED index is known, the set of 2D-3D point or zi−pi correspondences must be solved through the Perspective-n-Point (PnP) problem. The goal of this step is to estimate the full six degree of freedom rigid body transformation from the positioning stripe 30 to the camera coordinate system.
Referring to
z
i
=f(RWC,tWC,pi,α)
where f is a non-linear measurement function, RWC and TWC are the unknown camera orientation and position respectively, and a is a set of camera calibration parameters that fit the fisheye camera model. Additionally, extended Kalman filter (EKF) is used to track the camera pose [RWC|TWC] over subsequent time steps
According to another embodiment, the UAV positioning system comprises two flexible positioning stripes 30a, 30b adapted to be arranged in parallel along a predefined path as shown in
As shown in
More particularly, as the position/velocity of the UAV and the positions of the LEDs are known, the LEDs which are the closest to the image centre, thereafter the “middle LED”, capture by the camera sensor 16 in the next time step may be determined. As each LED belongs to a group of LEDs, which group the middle LED belongs to may be determined, so-called “middle group” thereafter. One or more groups of LEDs trailing the middle group and one or more groups of LEDs ahead of the middle group may be selectively controlled.
For example, assuming that a group of LEDs comprises 10 LEDs, LED 437 is the “middle LED” in the next time step, so group 430-439 is the middle group and LEDs 400-469 are selectively turned on.
In an advantageous embodiment, the positioning stripe 30 is made of several removably coupled segments in order to provide a length-adjustable positioning stripe. The positioning stripe 30 is therefore scalable with no theoretical upper bound on the positioning stripe length. The total length of the positioning stripe may therefore be adapted according to the application.
The positioning stripe 30 serves also as a user interface for controlling the flight path of the drone. We can use the information of the 3D shape of the stripe for planning the desired drone trajectory. The xy-dimension of the stripe will be mapped one on one to the desired flight path, while the height (z-dimension) can be a function of x and y resulting in z=f(x, y), controlled manually z=f(u) or kept constant z=C.
The invention is not limited to the above described embodiments and may comprise alternative within the scope of the appended claims. For example, active markers in the form of LEDs may be replaced by passive markers (e.g. reflective markers). Although, passive markers would not offer the possibility to actively communicate with the UAV, they would still encode position information and therefore fulfil the main purpose of the positioning stripe, which is enabling self-localization of the UAV.
Without the ability to communicate through the positioning stripe another communication channel may be used, such as a radio channel, in order to control the UAV interactively along the positioning stripe. Alternatively, a flight itinerary could be pre-programmed. For example, a flight itinerary may be pre-programmed, whereby the UAV is instructed to fly to the end of the stripe, whereupon the UAV hovers for a given period of time and return back to the start. In this case, no communication channel to the UAV is needed as all computations to fulfil the flight itinerary can be done onboard.
Number | Date | Country | Kind |
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00158/20 | Feb 2020 | CH | national |
Filing Document | Filing Date | Country | Kind |
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PCT/IB2021/050719 | 1/29/2021 | WO |