WO2024252365A1 - Engin autonome avec capteurs - Google Patents
Engin autonome avec capteurs Download PDFInfo
- Publication number
- WO2024252365A1 WO2024252365A1 PCT/IB2024/055617 IB2024055617W WO2024252365A1 WO 2024252365 A1 WO2024252365 A1 WO 2024252365A1 IB 2024055617 W IB2024055617 W IB 2024055617W WO 2024252365 A1 WO2024252365 A1 WO 2024252365A1
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- Prior art keywords
- processing
- data
- sensor
- processing circuitry
- machine
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/50—Service provisioning or reconfiguring
Definitions
- the present invention generally relates to autonomous devices, for example of the aerial drone type (or UAV for “Unmanned Aerial Vehicle” in English), equipped with sensors.
- such devices can be equipped with sensors for measuring environmental data (meteorological data such as wind, humidity, temperature, brightness, cloudiness, pollutants, radioactivity, radiofrequency signals, to name just a few examples), or image sensors (in the visible or non-visible ranges).
- environmental data metaleorological data such as wind, humidity, temperature, brightness, cloudiness, pollutants, radioactivity, radiofrequency signals, to name just a few examples
- image sensors in the visible or non-visible ranges
- an autonomous piloted aerial vehicle comprising motorized propulsion means, a control unit for the propulsion means to cause the vehicle to follow a flight trajectory provided by a piloting unit, the vehicle further comprising at least one sensor capable of delivering data requiring digital processing, the vehicle being provided with on-board digital processing circuitry, and being connected to at least one remote processing circuitry via a wireless communication network, the vehicle being characterized in that it comprises:
- a distribution circuit capable of directing data from the or each sensor to the on-board processing circuitry or to the remote processing circuitry depending on at least one criterion among a type of processing to be carried out, a processing capacity of the on-board processing circuitry and of the remote processing circuitry, a processing availability of the on-board processing circuitry and of the remote processing circuitry, a capacity of the wireless communication network, an availability of the wireless communication network, a data processing rate instruction,
- circuitry for recombination of data processed by the on-board processing circuitry and the remote processing circuitry, and - an interface circuit with the control unit, the latter being configured to take into account said recombined processed data at a given time and generate instructions for adjusting the behavior of the machine.
- said interface circuit is configured to generate a map of the recombined processed data, with a view to dynamically determining the trajectory of the machine.
- the adjustment instructions comprise flight adjustment instructions capable of modifying the limits of a scan of an area with the craft, and/or the speed of movement of the craft, and/or the precision of the path of the scanned area.
- the data provided by at least one sensor are data characterizing the atmosphere of the area.
- the processing to be carried out on the data from at least one sensor comprises algorithmic processing.
- the algorithmic processing comprises at least one of a spectral decomposition processing, a matrix calculation processing, a learning-based processing, a graph traversal processing.
- At least one criterion is determined using a processing resource management device.
- the processing resource management device implements a management protocol using a signaling channel of the wireless communication network.
- FIG. 1 is a schematic perspective view of a machine according to the invention
- Fig. 2 is a block diagram of the digital architecture of a device according to the invention and of digital resources available remotely,
- FIG. 3 is a more detailed block diagram of a particular implementation of the digital architecture of Fig. 2, and
- Fig. 4 is a detailed block diagram of a possible implementation of on-board and off-board processing resources.
- an autonomous flying machine E or drone here of the six-rotor type, which comprises a main body 10 and a set of arms 20 supporting as many rotors 30 each equipped with a propeller 31.
- a machine comprises an inertial unit 40 capable of delivering kinematic data, and a positioning unit 50 for example to the GPS standard capable of delivering universal positioning data. It is also conventionally equipped with one or more cameras 60 whose images are sent back to the ground by an appropriate communication channel.
- the device finally comprises one or more electronic cards 100, ensuring, in a manner known per se, the functions of autopilot, wireless communication with a non-embedded digital environment and in particular a ground station, and various on-board calculation means with processors, memories, input/output interfaces, etc.
- the assembly is powered by one or more rechargeable batteries not shown.
- the drone is equipped with a set of other sensors, here three sensors C1, C2, C3, which we will call here “business” sensors depending on the type of application envisaged.
- sensors can be based on extremely diverse technologies, in particular physical, optical, acoustic, chemical, and deliver data which, after possible formatting, are constituted of digital data of varying volume, at rates that can vary greatly.
- the sensors C1, C2, C3 deliver signals S1, S2, S3 which can be pre-processed at the level of dedicated circuits or units 1110, 1120, 1130 (or possibly a common circuit).
- Such pre-processing can consist of different operations chosen in particular from an analog/digital conversion, a normalization, a filtering, a formatting, etc. depending on the type of sensor and the design of the processing circuits located downstream.
- this preprocessing may comprise, for example, operations such as formatting in the form of messages each containing a data field containing the data to be processed from a sensor, sensor identifier information, time stamp information, scheduling data, derived for example from the time stamp data, and any other useful data or metadata, such as (i) data provided by other elements such as an inertial unit, other sensors conventionally equipping the machine and not requiring processing, such as a temperature sensor or distance sensors, and/or (ii) data indicative of the digital processing capacity required for the data contained in the message.
- operations such as formatting in the form of messages each containing a data field containing the data to be processed from a sensor, sensor identifier information, time stamp information, scheduling data, derived for example from the time stamp data, and any other useful data or metadata, such as (i) data provided by other elements such as an inertial unit, other sensors conventionally equipping the machine and not requiring processing, such as a temperature sensor or distance sensors, and/or (ii) data indicative of the digital processing capacity required for the
- Each unit 1110, 1120, 1130 can also, depending on the type of data received from a sensor, or the type of sensor that generated the data, insert into the message data representative of processing instructions to be executed, for example in the form of the address of a subroutine to be executed at the level of a local processing circuit (typically in “edge computing” in English terminology) or a remote processing circuit.
- a local processing circuit typically in “edge computing” in English terminology
- a remote processing circuit typically in “edge computing” in English terminology
- interpolation techniques are used, for example, to resynchronize them.
- the pre-processing unit is integrated into the sensor.
- the digital signals SPT1, SPT2, SPT3 output from the preprocessing circuits 1110, 1120, 1130 are received by a distribution circuit 1200.
- This circuit 1200 is configured to route the signals SPT1, SPT2, SPT3 to a digital signal processing resource chosen from a set of digital processing resources.
- the digital processing operations can be of very diverse natures, and more or less heavy depending on the nature of the processing and the volume of data contained in the signals SPT1, SPT2, SPT3. For example, they can be spectral decompositions, vector or matrix calculations, statistical calculations, etc., in the time and/or spatial domains. These processes can also implement deep learning mechanisms.
- a first resource comprises digital processing means 1300 on board the machine (processor(s) and memory). These means may be means shared with other on-board processing, or dedicated means.
- these embedded processing means advantageously comprise parallel processors according to “multi-core” architectures.
- a second digital processing resource 2300 is located in a remote digital processing environment 2000, with which the machine communicates via a wireless transmission channel WCC according to an appropriate technology.
- a preferred transmission channel is based on cellular technologies of the “5G” type.
- remote digital processing means are here implemented in a radio network environment (RAN for “Radio Access Network” in English), one of the important aspects being the flow rate and the speed of communication via the WCC channel and the processing speed at the level of the remote processing means.
- RAN Radio Network
- these remote digital processing means are implemented in a wide area network environment, such as a "cloud" environment, with potentially unlimited available resources and processing speeds dependent on network transmission throughput and latency.
- These different processing means are capable of executing on the preprocessed signals SPT1, ST2, ST3, distributed by the circuit 1200, different types of processing, as indicated above.
- a single sensor C1 is shown, here a gas sensor, which generates raw data S1 which are collected by the preprocessing unit 1110 which can consist of a pipelined processor.
- This unit 1110 includes:
- module 1112 configured to add to the raw data different types of metadata, for example data included in a group comprising the GPS coordinates of the machine, its altitude, its speed, wind data (obtained by a specific sensor or from another data source), by carrying out the necessary interpolations in cases where this information is delivered at different rates, and by generating messages of appropriate format and
- a remote processing unit 2300 deployed at the level of an architecture 2000 accessible by a RAN radio network to which the device is connected, with for example a cellular network architecture of the “5G” type, and another remote processing unit 3300 deployed at the level of a wide area network environment 3000 of the “Cloud” type, which can include reduced latency processing means of the “Edge Network” type.
- the distribution unit 1200 carries out the distribution according to at least one criterion.
- a preferred criterion is the need to ensure real-time or quasi-real-time processing of the data produced by the sensor C1, particularly in the case where this processing is likely to impact the trajectory of the machine, as will be detailed below.
- the distribution of the data messages to be processed is carried out according to a latency criterion and information on availability and/or capacity of the processing units 1300, 2300, 3300.
- the distribution unit can simply reject certain messages, which will not be processed but which can nevertheless be stored for later processing at a later time.
- the distribution unit can send the data messages to be processed to the local processing unit 1300, monitor the return from this unit in terms of latency and possibly messages unprocessed, and in the event that the latency becomes greater than a certain threshold, distribute the data messages to be processed between the local unit 1300 and the remote processing units 2300, 3300.
- the distribution keys can be dynamically adjusted according to the latency measured at the level of the return messages from the processing units.
- the above criterion can undergo many variations. For example, we can favor the processing unit 2300 located at the radio network level, for the reliability of its connection with the machine, or even the processing unit located at the “Cloud” level, for its potentially unlimited processing capacity, with however a greater exposure to latency phenomena.
- the circuits embedded in the machine can determine a processing capacity per unit of time required, based on a certain number of criteria.
- the on-board circuitry can calculate the speed that the device must have to travel the entire path taking into account its available autonomy (with a safety margin), which in turn determines the frequency at which the sensor will send data to be processed (the higher the speed must be, the higher the frequency will increase and the greater the volume of data to be processed per unit of time will be).
- the distribution unit will decide to allocate the necessary resources between the local processing unit 1300 and the remote processing units 2300, 3300 so that this volume of data can be processed.
- the recording unit (log function) of the sensor data is designated by the reference 1500. It comprises a unit 1510 for storing the raw data (here the signals S1 collected at the level of the unit 1111) and a unit 1520 for storing the processed data. [0066] In delayed time, this data can be transmitted in batches to the processing means 2300 and/or 3300 for additional processing.
- the metadata insertion module 1112 may also incorporate preprocessing functions that may include:
- an interpolation which is implemented in the case of several sensors operating at different frequencies, and possibly non-synchronously (particularly in the case of sensors having their own clock);
- the processed data messages sent by the processing means 1300, 2300, 3300 are recovered at the reordering/recombining unit 1400 (illustrated in FIG. 3 as being located in the same block as the unit 1200) and reordered by the unit 1400 thanks in particular to the order numbers appearing in the messages.
- the unit 1400 is associated with a latency management unit 1250, for example by rejecting packets received beyond a certain delay (TTL) and/or packets received out of order (“jitter”).
- TTL delay
- jitter packets received out of order
- the unit 1400 is connected via the unit 1250 on the one hand to the memory 1520 of processed data of the recording unit 1500, and on the other hand to a message agent 1600 (“message broker” in English) responsible for routing the messages as will now be described.
- a message agent 1600 (“message broker” in English) responsible for routing the messages as will now be described.
- the agent 1600 redirects the messages (or certain messages, depending on their types) to a data analysis module 1700 configured to extract from the succession of messages processed by the units 1300, 2300, 3300 a certain number of metrics which can be extremely varied: average noise level, spectral decomposition with a view to detecting gas concentration peaks, sound signatures (case of acoustic sensors), spectral signatures in visible or invisible radiation, etc.
- the module 1700 can also be configured to perform different kinds of post- processing on the recombined processed signals, these processings being able to include filtering, noise elimination, threshold detections, the creation of measurement maps, etc. Alternatively or in addition, such processings can also be carried out at the level of the recombination unit 1400.
- the agent 1600 also redirects the messages received from the unit 1250 and likely to impact the navigation of the machine, as well as analysis messages from the module 1700, to a navigation module 1800.
- This module 1800 comprises a set of software 1100 (software stack) ensuring the navigation of the craft by generating piloting commands based either on flight instructions received from a ground station, or on the geolocation of the craft E and a trajectory to be followed, stored or dynamically generated based on a certain number of criteria including the flight environment.
- the module 1800 applies the flight instructions CV to a flight controller 1900, which returns telemetry values TM to the module 1800 in a manner known per se.
- this module 1800 is also configured to adapt the behavior of the craft E according to the measurements made by the sensor C1 after processing by the means 1300, 2300, 3300 and, where appropriate, analysis by the module 1700.
- this adaptation includes an automatic adjustment of the trajectory of the craft (with respect to a set trajectory in the case of an autonomous flight). For example, when the sensor C1 and the associated processing are designed to perform an environmental measurement (physical, optical, chemical, radioactivity parameters, etc.), the trajectory of the craft can be modified (turn back, travel another imposed line, etc.) when the processed sensor data show that the measured information becomes lower than a certain threshold and over a certain extent and/or for a certain duration.
- the machine typically includes a wind sensor to determine by calculation, using the wind vector, the orientation of the vertical (or possibly inclined) plane containing the path of the machine.
- the measurements made at one of the sensors may lead to temporarily ceasing to make other measurements using another sensor, either because these other measurements become useless or less relevant, or to reserve a greater part of the processing capacity for the data of a particular sensor, if necessary by increasing its sampling and processing time frequency and/or by decreasing its measurement step. This may be done either within the unit 1800, or in a specific sensor management unit, not illustrated.
- the sensor data can be applied in whole or in part to an artificial intelligence, hosted in one or more of the processing units 1300, 2300, 3300, intended to adjust the operating conditions of the machine and the operation of the sensors (modification of the trajectory and speed of the machine, starting or stopping a certain capture, modification of the capture frequency, choice of the processing unit among the processing units 1300, 2300, 3300 for the data from each of the sensors, with, where appropriate, specific arbitration rules).
- an artificial intelligence hosted in one or more of the processing units 1300, 2300, 3300, intended to adjust the operating conditions of the machine and the operation of the sensors (modification of the trajectory and speed of the machine, starting or stopping a certain capture, modification of the capture frequency, choice of the processing unit among the processing units 1300, 2300, 3300 for the data from each of the sensors, with, where appropriate, specific arbitration rules).
- the reference 2000 designates the off-board digital processing environment, connected to the machine. via a radio network architecture and capable of contributing to the pre-processed signal processing available at the distribution module 1200.
- the digital processing resources themselves are designated by the reference 2300 and will be described in more detail below.
- reference 3000 designates the off-board digital processing environment, connected to the machine via a “Cloud” type architecture and also capable of contributing to the processing of pre-processed signals available at the level of the distribution module 1200.
- the digital processing resources themselves are designated by reference 3300 and will be described in more detail below.
- API application programming interface
- the environment 3000 can execute the processing algorithms in deferred time after having downloaded the raw data.
- the “Cloud” environment 3000 comprises a gateway 3100 with the engine E, which is connected to a set of data management services 3200.
- the data is routed to a sensor data processing service 3400 which makes the connection with the processing means 3300.
- the services 3200 are also connected to databases 3500, application programming interface (API) gateways 3600 for cooperation with third-party applications 3650, and client gateways 3700 for cooperation with client stations 3750.
- API application programming interface
- an architecture has been illustrated which may be common to the processing means 1300, 2300, 3300. [0085] It comprises a secure proxy 310 and a processing architecture 320 comprising a manager 321 of the computing load cooperating with a planning unit ("scheduler" in English) 322, and a set of processing cores 323a-323h. As illustrated in the left part of FIG. 4, each processing core comprises an input/output interface 324 and a processor 325 executing a certain algorithm, receiving the input data DE resulting from the pre-processing and restoring the output data DS which will return to the reordering/recombination unit 1400.
- availability data can be determined by a calendar, response time measurements, etc.
- each accessible processing device being able to receive a request to this effect
- this common resource management device is implemented by relying on the signaling channels of the networks implemented.
- certain types of sensor data to be processed can advantageously be subject to compression and/or encryption before being sent to a remote processing unit 2300 or 3300.
- the data from the sensors can be signed in order to certify their authenticity.
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Abstract
Description
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Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| EP24738057.9A EP4724895A1 (fr) | 2023-06-07 | 2024-06-07 | Engin autonome avec capteurs |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| FRFR2305752 | 2023-06-07 | ||
| FR2305752A FR3149716A1 (fr) | 2023-06-07 | 2023-06-07 | Engin autonome avec capteurs |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2024252365A1 true WO2024252365A1 (fr) | 2024-12-12 |
Family
ID=89308070
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/IB2024/055617 Ceased WO2024252365A1 (fr) | 2023-06-07 | 2024-06-07 | Engin autonome avec capteurs |
Country Status (3)
| Country | Link |
|---|---|
| EP (1) | EP4724895A1 (fr) |
| FR (1) | FR3149716A1 (fr) |
| WO (1) | WO2024252365A1 (fr) |
-
2023
- 2023-06-07 FR FR2305752A patent/FR3149716A1/fr active Pending
-
2024
- 2024-06-07 EP EP24738057.9A patent/EP4724895A1/fr active Pending
- 2024-06-07 WO PCT/IB2024/055617 patent/WO2024252365A1/fr not_active Ceased
Non-Patent Citations (2)
| Title |
|---|
| JUNG WOO-SUNG ET AL: "ACODS: adaptive computation offloading for drone surveillance system", 2017 16TH ANNUAL MEDITERRANEAN AD HOC NETWORKING WORKSHOP (MED-HOC-NET), IEEE, 28 June 2017 (2017-06-28), pages 1 - 6, XP033139313, DOI: 10.1109/MEDHOCNET.2017.8001647 * |
| LI HUANRAN ET AL: "Optimal Offloading of Computing-intensive Tasks for Edge-aided Maritime UAV Systems", 2022 IEEE 95TH VEHICULAR TECHNOLOGY CONFERENCE: (VTC2022-SPRING), IEEE, 19 June 2022 (2022-06-19), pages 1 - 6, XP034175722, DOI: 10.1109/VTC2022-SPRING54318.2022.9860881 * |
Also Published As
| Publication number | Publication date |
|---|---|
| EP4724895A1 (fr) | 2026-04-15 |
| FR3149716A1 (fr) | 2024-12-13 |
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