WO2018094312A1 - System and method for detecting humans by an unmanned autonomous vehicle - Google Patents
System and method for detecting humans by an unmanned autonomous vehicle Download PDFInfo
- Publication number
- WO2018094312A1 WO2018094312A1 PCT/US2017/062500 US2017062500W WO2018094312A1 WO 2018094312 A1 WO2018094312 A1 WO 2018094312A1 US 2017062500 W US2017062500 W US 2017062500W WO 2018094312 A1 WO2018094312 A1 WO 2018094312A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- energy
- sensor
- human
- sensed
- unmanned vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/0055—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots with safety arrangements
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/04—Control of altitude or depth
- G05D1/06—Rate of change of altitude or depth
- G05D1/0607—Rate of change of altitude or depth specially adapted for aircraft
- G05D1/0653—Rate of change of altitude or depth specially adapted for aircraft during a phase of take-off or landing
- G05D1/0676—Rate of change of altitude or depth specially adapted for aircraft during a phase of take-off or landing specially adapted for landing
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/251—Fusion techniques of input or preprocessed data
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/254—Fusion techniques of classification results, e.g. of results related to same input data
- G06F18/256—Fusion techniques of classification results, e.g. of results related to same input data of results relating to different input data, e.g. multimodal recognition
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/10—Image acquisition
- G06V10/12—Details of acquisition arrangements; Constructional details thereof
- G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
- G06V10/143—Sensing or illuminating at different wavelengths
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
- G06V10/803—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of input or preprocessed data
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
- G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
- G06V10/809—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data
- G06V10/811—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level of classification results, e.g. where the classifiers operate on the same input data the classifiers operating on different input data, e.g. multi-modal recognition
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/13—Satellite images
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/17—Terrestrial scenes taken from planes or by drones
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/103—Static body considered as a whole, e.g. static pedestrian or occupant recognition
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft
- G08G5/20—Arrangements for acquiring, generating, sharing or displaying traffic information
- G08G5/21—Arrangements for acquiring, generating, sharing or displaying traffic information located onboard the aircraft
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft
- G08G5/50—Navigation or guidance aids
- G08G5/55—Navigation or guidance aids for a single aircraft
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft
- G08G5/50—Navigation or guidance aids
- G08G5/57—Navigation or guidance aids for unmanned aircraft
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G5/00—Traffic control systems for aircraft
- G08G5/80—Anti-collision systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/18502—Airborne stations
- H04B7/18506—Communications with or from aircraft, i.e. aeronautical mobile service
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U2101/00—UAVs specially adapted for particular uses or applications
- B64U2101/60—UAVs specially adapted for particular uses or applications for transporting passengers; for transporting goods other than weapons
- B64U2101/64—UAVs specially adapted for particular uses or applications for transporting passengers; for transporting goods other than weapons for parcel delivery or retrieval
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
- B64U2201/00—UAVs characterised by their flight controls
- B64U2201/10—UAVs characterised by their flight controls autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
Definitions
- This invention relates generally to unmanned vehicles such as aerial drones, and more particularly, to approaches for detecting humans by unmanned vehicles.
- Drones When an aerial drone flies in an environment where people are likely to be present, the drone must avoid these people to avoid injury to the people, and possible damage to the drones. Drones sometimes deploy technology that senses people and objects, and helps the drone avoid the people and objects as the drone moves within a given environment.
- Some of these approaches rely upon using cameras to obtain images of the environment of the drone, and then determining whether humans are present in these images. Unfortunately, the quality of these images is often not good, and this can lead to either false identifications of humans (when humans are, in fact, not present in the image), or completely missing the detection of humans (when the humans are actually present in the image).
- FIG. 1 is a block diagram of a system that determines the presence of a human by an unmanned vehicle in accordance with some embodiments
- FIG. 2 is a block diagram of an unmanned vehicle that determines the presence of a human in accordance with some embodiments
- FIG. 3 is a flowchart of an approach that determines the presence of a human in accordance with some embodiments
- FIG. 4 is a flowchart of an approach showing details of correlating a fused image with radio frequency (RF) data in accordance with some embodiments
- FIG. 5 is one example of a fused image including both visible and infrared data in accordance with some embodiments
- FIG. 6 are graphs of RF data used to determine the presence of a human in accordance with some embodiments.
- FIG. 7 is a block diagram of an apparatus that determines the presence of a human in accordance with some embodiments.
- systems, apparatuses and methods are provided herein for determining the presence of a human and/or any other living being such as animals by an unmanned autonomous vehicle (such as an aerial drone). These approaches are reliable and allow the accurate identification of a human within the operating environment of an unmanned vehicle.
- Infrared and visible light data is fused together into a fused composite pseudo-IR image, which the drone may search for objects that look approximately like people (via computer vision algorithms well-known in the art) and that have the temperature properties expected of people (e.g., exposed skin typically being in the 80-90 degree F range).
- a scan is also made for radio frequency (RF) energy emitted by wireless devices likely to be carried by a human.
- RF energy may be sensed by a small software defined radio (SDR) capable of fast scanning RF bands, which will have uplink energy from a cellphone on them.
- SDR software defined radio
- the RF regions of interest may include cellular bands (e.g., across the various 2G, 3G, 4G bands, Bluetooth, and Wi-Fi bands). Other examples are possible.
- any discovery of uplink energy by the unmanned vehicle may (with some signal processing to determine a line of bearing from the drone to the cellular phone) be correlated and fused with the fused composite pseudo-IR image to determine the presence of a human and thus avoid the human.
- the unmanned vehicle is equipped with the capability to use RSSI and/or multilateration based technology to determine the position of the unmanned vehicle. These approaches may receive Wi-Fi signals broadcast in, for example, residential and commercial buildings.
- the unmanned vehicle may use the received signal strength of a wireless device to determine the distance to that device and to stay a safe distance from human associated with that device.
- an unmanned vehicle e.g., an aerial drone or ground vehicle
- delivers packages or other payloads includes a first sensor, a second sensor, a third sensor, and a control circuit.
- the first sensor is configured to sense infrared energy
- the second sensor is configured to sense visible light viewable by a human observer.
- the third sensor is configured to sense RF energy from a mobile wireless device.
- the control circuit is coupled to the first sensor, the second sensor, and the third sensor, and is configured to determine the presence of a human associated with the mobile wireless device using the sensed infrared energy, the sensed visible light, and the sensed RF energy.
- control circuit is configured to produce a composite image by fusing together the sensed infrared energy and the sensed visible light energy.
- the control circuit is further configured to analyze the composite image for the presence of a human form, and analyze the sensed RF energy for the presence of uplink energy produced by the mobile wireless device.
- the control circuit may be further configured to correlate the uplink energy with the human form to determine the presence of the human associated with the mobile wireless device carried by the human form.
- control circuit is configured to determine a line of bearing to the mobile wireless device. In other examples, the control circuit determines a distance to the wireless device.
- the composite image presents temperature properties that are associated with humans and a visible image showing the same field of view as the infrared image. Selected portions of the infrared image and/or the visible image may be used to that the composite image does not become unreadable.
- control circuit is configured to create electronic control signals that are effective to maneuver the unmanned vehicle so as to avoid a collision with the human.
- the control circuit forms electronic control signals that are effective to control the operation of the unmanned vehicle so as to maintain a predetermined distance between the human and the unmanned vehicle.
- control circuit determines the received signal strengths of RF signals received from the mobile wireless device and the received signal strengths are used to form the electronic control signals.
- the system 100 includes a drone 102 (including sensors 104), a person 106 (with a wireless device 108), an unmanned vehicle 122 (with sensors 124), and products 130.
- a drone 102 including sensors 104
- a person 106 with a wireless device 108
- an unmanned vehicle 122 with sensors 124
- products 130 the system of FIG. 1 is deployed in a warehouse or store. However, it will be appreciated that these elements may be deployed in any interior or exterior setting.
- the drone 102 is an unmanned autonomous vehicle that is configured to navigate by itself without any centralized control.
- the drone 102 may include any type of propulsion system (such as engine and propellers), and can fly in both interior and exterior spaces.
- the unmanned vehicle 122 is an unmanned autonomous vehicle that is configured to navigate by itself without any centralized control.
- the drone unmanned vehicle 122 may include any type of propulsion system so that it can move on the ground in any exterior or interior space.
- the products 130 may be any type of consumer product that is situated in a warehouse or store.
- the sensors 104 and 124 include sensors to sense visible light 110, infrared energy
- the wireless device 108 is any type of mobile wireless service such as a cellular phone, tablet, personal digital assistant, or personal computer. Other examples are possible.
- the sensors 104 and 124 sense visible light 1 10, infrared energy 112, and RF energy (from the wireless device 108 and possibly from other sources).
- a composite image is produced at the drone 102 or the unmanned vehicle 122.
- the composite image is produced by fusing together the sensed infrared energy and the sensed visible light energy.
- the composite image is analyzed for the presence of a human form.
- the sensed RF energy 1 14 is analyzed for the presence of uplink energy produced by the mobile wireless device 108.
- the uplink energy is correlated with the human form to determine the presence of the human 106 associated with the mobile wireless device 108 carried by the human 106.
- the unmanned vehicle 202 includes an infrared sensor 204, a visible light sensor 206, an RF energy sensor 208, a control circuit 210, and a navigation control circuit 212.
- the unmanned vehicle 202 may be an aerial drone or a ground vehicle. In either case, the unmanned vehicle 202 is configured to navigate by itself without any centralized control.
- the infrared sensor 204 is configured to detect energy in the infrared frequency range.
- the visible light sensor 206 is configured to sense light and images in the frequency range that is visible by humans.
- the RF energy sensor 208 is configured to sense uplink energy in frequency bands utilized by wireless devices (e.g., cellular frequency bands).
- the navigation control circuit 212 may be implemented as any combination of hardware or software elements.
- the navigational control circuit 212 includes a microprocessor that executes computer instructions stored in a memory.
- the navigation control circuit 212 may receive instructions or signals from the control circuit 210 as to where to navigate the vehicle 202. Responsively, the navigation control circuit 212 may adjust propulsion elements of the vehicle 202 to follow these instructions. For example, the navigation control circuit 212 may receive instructions from the control circuit 210 to turn the vehicle 45 degrees, and adjust the height of the vehicle to 20 feet (assuming the vehicle is a drone).
- the navigation control circuit 212 causes the vehicle 202 to turn 45 degrees and activates an engine 209 and a propulsion apparatus 215 (e.g., the propellers) to adjust the height to 20 feet.
- the engine 209 may be any type of engine using any type of fuel or energy to operate.
- the propulsion element 215 may be any device or structure that is used to propel, direct, and/or guide the vehicle 202.
- the vehicle 202 includes a cargo 213, which may be, for example, a package.
- control circuit refers broadly to any microcontroller, computer, or processor-based device with processor, memory, and programmable input/output peripherals, which is generally designed to govern the operation of other components and devices. It is further understood to include common accompanying accessory devices, including memory, transceivers for communication with other components and devices, etc. These architectural options are well known and understood in the art and require no further description here.
- the control circuit 210 may be configured (for example, by using corresponding programming stored in a memory as will be well understood by those skilled in the art) to carry out one or more of the steps, actions, and/or functions described herein.
- the control circuit 210 is configured to receive sensed information from the infrared sensor 204, visible light sensor 206, and RF energy sensor 208 and, if required provide any conversion functions (e.g., convert any analog sensed data into digital data that can be utilized and processed by the control circuit 210).
- the control circuit 210 is configured to determine the presence of the human 214 associated with a mobile wireless device 216 (e.g., a cellular phone, tablet, personal digital assistant, or personal computer to mention a few examples) using the sensed infrared energy, the sensed visible light, and the sensed RF energy.
- a mobile wireless device 216 e.g., a cellular phone, tablet, personal digital assistant, or personal computer to mention a few examples
- control circuit 210 is configured to produce a composite image by fusing together the sensed infrared energy and the sensed visible light energy.
- the creation of composite images (e.g., laying one image over another image) is well known to those skilled in the art.
- the control circuit 210 is further configured to analyze the composite image for the presence of a human form and analyze the sensed RF energy for the presence of uplink energy produced by the mobile wireless device 216.
- the control circuit 210 may be further configured to correlate the uplink energy with the human form to determine the presence of the human 214 associated with the mobile wireless device 216 carried by the human 214.
- control circuit 210 is configured to determine a line of bearing to the mobile wireless device 216. In other examples, the control circuit 210 determines a distance to the wireless device 216.
- the composite image presents temperature properties that are associated with the human 214 and a visible image of the same field of view as the infrared image. Selected portions of the infrared image and/or the visible image (rather than the entirety of either image may be used so that the composite image does not become unreadable by attempting to present too much information. For example, irrelevant information (e.g., details from inanimate objects, or reflections) from the visible image may be ignored and not used in the composite image.
- irrelevant information e.g., details from inanimate objects, or reflections
- control circuit 210 is configured to create electronic control signals (sent to navigation control circuit 212 via connection 211) that are effective to maneuver the unmanned vehicle so as to avoid a collision with the human.
- control circuit 210 forms electronic control signals (sent to navigation control circuit 212 via connection 211) that are effective to control the operation of the unmanned vehicle 202 so as to maintain a predetermined distance between the human 214 and the unmanned vehicle 202.
- control circuit 210 determines the received signal strengths of RF signals received from the mobile wireless device 216 and the received signal strengths are used to form the electronic control signals.
- Infrared data 304 and visible light data 306 are fused together at step 302.
- the result of this step is the creation of a fused image 308.
- the fused image includes both infrared data and visible light data.
- the fused image 308 is searched for a human form. This can be accomplished, for example, by using image analysis software that is well known to those skilled in the art. Once the human form is found in the fused image, the form is correlated with RF data 310.
- the presence of a human is determined. For example, when a certain detected RF energy amount exceeds a threshold and matches a position of the human form, a determination may be made that a human is present.
- the unmanned vehicle is navigated to avoid the human.
- the propulsion system in the vehicle may be controlled and directed to cause the vehicle to take a route that avoids contact with the human.
- FIG. 4 one example of an approach showing details of correlating a fused image with RF data is described.
- fused data is obtained.
- the fused data is a composite image formed from sensed infrared data and sensed visible light data.
- the RF data includes uplink data that may be from a wireless device operated by a human.
- Well-known image analysis software may be used to analyze the composite image. For example, a search may be made for an area in the image having certain thermal properties (e.g., the temperature for humans), and for imagery that matches human physical elements (e.g., heads, bodies, arms, legs, and so forth). If the analysis determines that the human physical elements exist at a human temperature range, it may be determined that a human form exists in the composite image.
- the RF data is examined to determine whether the energy is from a wireless device (e.g., it is not background noise).
- the directionality of uplink energy from the sensor is also made using known techniques. A determination may then be made as to whether the human form detected at step 406 correlates with the direction of the energy.
- FIG. 5 one example of a fused or composite image (with both visible and infrared data) is described.
- the fused image shown in FIG. 5 includes both visible light imagery and infrared light imagery, and is of an outdoor scene.
- the infrared light imagery is represented over a spectrum of shadings (or colors) with the darkest shade (or color) representing the coldest temperature and the brightest or lightest shade (or color) representing the warmest temperature for objects. In other words, different shades (or colors) represent different temperatures.
- Both the visible light image and the infrared image have the same field of view.
- one particular shading may correspond the temperatures of the human body.
- a visible light image is overlaid onto the infrared image. It will be realized that varying amounts of data from the visible light image may be overlaid onto the infrared image. For example, if too much visible light data is included the fused image, then the fused image may become unreadable or unusable. As a result, selective portions of each of the visible light image and infrared image may be used to form the fused image.
- the fused image includes human figures 502, 504, 506, 508, and 510.
- these figures 502, 504, 506, 508, and 510 are of a lighter color (indicating a greater temperature than the background environment). It will also be appreciated that discernable human features (e.g., arms, legs, and heads, to mention a few examples) are discernable because a visible light image is part of the fused image. The visible light image also helps in discerning paths, sidewalks, trees, and bushes in the example image of FIG. 5.
- FIG. 5 shows a view outdoors, but that these approaches are applicable to indoor locations (e.g., the interior of warehouse or stores). Additionally, the image of FIG. 5 shows a fused image at a somewhat long distance. It will be appreciated that the approaches are applicable at much shorter distances (where these approaches may not only determine the presence of a human, but other information about the human such as their height, weight, or identity).
- FIG. 6 graphs of RF data used to determine the presence of a human are described.
- the top graph shows a plot of frequency versus response while the bottom graph shows a histogram of frequencies.
- RF energy spikes at frequencies 602, 604, and 606 indicating one or more possible wireless devices.
- the direction of this energy from the unmanned device may be determined as can be the distance to the wireless device (e.g., using RSSI approaches that are well known in the art). All of this information can be correlated with a fused image to determine the presence of one or more humans.
- an apparatus 702 that determines the presence of a human
- the apparatus 702 includes an infrared sensor 704, a visible light sensor 706, an RF energy sensor 708, and a control circuit 710.
- the control circuit 710 may be coupled to another device 711 (e.g., a display device or a recording device to mention two examples).
- the apparatus 702 includes a housing that encloses (or has attached to it) some or all of these elements.
- the apparatus 702 may be stationary.
- the apparatus 702 may be permanently or semi-permanently attached to a wall or ceiling.
- the apparatus 702 may be movable.
- the apparatus may be attached to a vehicle, person, or some other entity that moves.
- the infrared sensor 704 is configured to detect energy in the infrared frequency range.
- the visible light sensor 706 is configured to sense light and images in the frequency range that is visible by humans.
- the RF energy sensor 708 is configured to sense uplink energy in frequency bands utilized by wireless devices (e.g., cellular frequency bands).
- control circuit refers broadly to any microcontroller, computer, or processor-based device with processor, memory, and programmable input/output peripherals, which is generally designed to govern the operation of other components and devices. It is further understood to include common accompanying accessory devices, including memory, transceivers for communication with other components and devices, etc. These architectural options are well known and understood in the art and require no further description here.
- the control circuit 710 may be configured (for example, by using corresponding programming stored in a memory as will be well understood by those skilled in the art) to carry out one or more of the steps, actions, and/or functions described herein.
- the control circuit 710 is configured to received sensed information from the infrared sensor 704, visible light sensor 706, and RF energy sensor 708 and, if required provide any conversion functions (e.g., convert any analog sensed data into digital data that can be utilized and processed by the control circuit 710).
- the control circuit 710 is configured to determine the presence of the human 714 associated with a mobile wireless device 716 (e.g., a cellular phone, tablet, personal digital assistant, or personal computer to mention a few examples) using the sensed infrared energy, the sensed visible light, and the sensed RF energy.
- a mobile wireless device 716 e.g., a cellular phone, tablet, personal digital assistant, or personal computer to mention a few examples
- control circuit 710 is configured to produce a composite image by fusing together the sensed infrared energy and the sensed visible light energy.
- the creation of composite images (e.g., laying one image over another image) is well known to those skilled in the art.
- the control circuit 710 is further configured to analyze the composite image for the presence of a human form and analyze the sensed RF energy for the presence of uplink energy produced by the mobile wireless device 716.
- the control circuit 710 may be further configured to correlate the uplink energy with the human form to determine the presence of the human 714 associated with the mobile wireless device 716 carried by the human 714.
- control circuit 710 is configured to determine a line of bearing to the mobile wireless device 716. In other examples, the control circuit 710 determines a distance to the wireless device 716.
- the composite image presents temperature properties that are associated with the human 714 and a visible image of the same field of view as the infrared image. Selected portions of the infrared image and/or the visible image (rather than the entirety of either image) may be used to that the composite image does not become unreadable by attempting to present too much information. For example, irrelevant information (e.g., details from inanimate objects, or reflections) from the visible image may be ignored and not used in the composite image.
- irrelevant information e.g., details from inanimate objects, or reflections
- the composite image and information concerning the location of the human 714 can be used in a variety of different ways.
- this information may be displayed at the device 711 for various purposes.
- the composite image and bearing information can be displayed at the device 711. This allows a person at the device 71 1 to avoid a collision with the human 714.
- the device 711 may be a smartphone and the person with the device 71 1 may be travelling in a vehicle, in one example.
- the composite image and information can be sent to other processing elements or devices, or used to control the operation of these devices.
- the information can be used to steer or otherwise direct a vehicle to avoid the human 714.
- the information can be reported (e.g., broadcast) to other humans or vehicles so that they can avoid the human 714.
Landscapes
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Multimedia (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Data Mining & Analysis (AREA)
- Remote Sensing (AREA)
- Artificial Intelligence (AREA)
- Evolutionary Computation (AREA)
- Business, Economics & Management (AREA)
- Astronomy & Astrophysics (AREA)
- Economics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- General Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Automation & Control Theory (AREA)
- Databases & Information Systems (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Computing Systems (AREA)
- Software Systems (AREA)
- Signal Processing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Human Resources & Organizations (AREA)
- Human Computer Interaction (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
Description
Claims
Priority Applications (4)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| MX2019005847A MX2019005847A (en) | 2016-11-21 | 2017-11-20 | System and method for detecting humans by an unmanned autonomous vehicle. |
| CN201780084142.2A CN110267720A (en) | 2016-11-21 | 2017-11-20 | Systems and methods for detecting humans by unmanned autonomous vehicles |
| CA3044252A CA3044252A1 (en) | 2016-11-21 | 2017-11-20 | System and method for detecting humans by an unmanned autonomous vehicle |
| GB1907683.5A GB2570613A (en) | 2016-11-21 | 2017-11-20 | System and method for detecting humans by an unmanned autonomous vehicle |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US201662424657P | 2016-11-21 | 2016-11-21 | |
| US62/424,657 | 2016-11-21 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2018094312A1 true WO2018094312A1 (en) | 2018-05-24 |
Family
ID=62146842
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/US2017/062500 Ceased WO2018094312A1 (en) | 2016-11-21 | 2017-11-20 | System and method for detecting humans by an unmanned autonomous vehicle |
Country Status (6)
| Country | Link |
|---|---|
| US (1) | US20180144645A1 (en) |
| CN (1) | CN110267720A (en) |
| CA (1) | CA3044252A1 (en) |
| GB (1) | GB2570613A (en) |
| MX (1) | MX2019005847A (en) |
| WO (1) | WO2018094312A1 (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108985687A (en) * | 2018-07-05 | 2018-12-11 | 北京智行者科技有限公司 | A kind of picking method for sending cargo with charge free |
| US11395232B2 (en) * | 2020-05-13 | 2022-07-19 | Roku, Inc. | Providing safety and environmental features using human presence detection |
| US11736767B2 (en) | 2020-05-13 | 2023-08-22 | Roku, Inc. | Providing energy-efficient features using human presence detection |
| US11202121B2 (en) | 2020-05-13 | 2021-12-14 | Roku, Inc. | Providing customized entertainment experience using human presence detection |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140254896A1 (en) * | 2011-07-18 | 2014-09-11 | Tiger T G Zhou | Unmanned drone, robot system for delivering mail, goods, humanoid security, crisis negotiation, mobile payments, smart humanoid mailbox and wearable personal exoskeleton heavy load flying machine |
| US20150054639A1 (en) * | 2006-08-11 | 2015-02-26 | Michael Rosen | Method and apparatus for detecting mobile phone usage |
| US20150094883A1 (en) * | 2012-12-28 | 2015-04-02 | Google Inc. | Multi-part Navigation Process by an Unmanned Aerial Vehicle for Navigation |
| US20150120057A1 (en) * | 2012-02-29 | 2015-04-30 | Irobot Corporation | Mobile Robot |
| US20160236778A1 (en) * | 2014-07-08 | 2016-08-18 | Google Inc. | Bystander Interaction During Delivery from Aerial Vehicle |
Family Cites Families (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9557742B2 (en) * | 2013-11-27 | 2017-01-31 | Aurora Flight Sciences Corporation | Autonomous cargo delivery system |
| US9696725B2 (en) * | 2013-12-13 | 2017-07-04 | SZ DJI Technology Co., Ltd | Methods for launching and landing an unmanned aerial vehicle |
| US9359074B2 (en) * | 2014-09-08 | 2016-06-07 | Qualcomm Incorporated | Methods, systems and devices for delivery drone security |
| US10387825B1 (en) * | 2015-06-19 | 2019-08-20 | Amazon Technologies, Inc. | Delivery assistance using unmanned vehicles |
| US10088736B2 (en) * | 2015-09-24 | 2018-10-02 | Amazon Technologies, Inc. | Unmanned aerial vehicle descent |
| US9963246B2 (en) * | 2016-03-28 | 2018-05-08 | Amazon Technologies, Inc. | Combining depth and thermal information for object detection and avoidance |
| JP6212663B1 (en) * | 2016-05-31 | 2017-10-11 | 株式会社オプティム | Unmanned aircraft flight control application and unmanned aircraft flight control method |
| US9977434B2 (en) * | 2016-06-23 | 2018-05-22 | Qualcomm Incorporated | Automatic tracking mode for controlling an unmanned aerial vehicle |
| US10520943B2 (en) * | 2016-08-12 | 2019-12-31 | Skydio, Inc. | Unmanned aerial image capture platform |
| US10049589B1 (en) * | 2016-09-08 | 2018-08-14 | Amazon Technologies, Inc. | Obstacle awareness based guidance to clear landing space |
| US10198955B1 (en) * | 2016-09-08 | 2019-02-05 | Amazon Technologies, Inc. | Drone marker and landing zone verification |
-
2017
- 2017-11-17 US US15/815,936 patent/US20180144645A1/en not_active Abandoned
- 2017-11-20 WO PCT/US2017/062500 patent/WO2018094312A1/en not_active Ceased
- 2017-11-20 CA CA3044252A patent/CA3044252A1/en not_active Abandoned
- 2017-11-20 CN CN201780084142.2A patent/CN110267720A/en active Pending
- 2017-11-20 MX MX2019005847A patent/MX2019005847A/en unknown
- 2017-11-20 GB GB1907683.5A patent/GB2570613A/en not_active Withdrawn
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150054639A1 (en) * | 2006-08-11 | 2015-02-26 | Michael Rosen | Method and apparatus for detecting mobile phone usage |
| US20140254896A1 (en) * | 2011-07-18 | 2014-09-11 | Tiger T G Zhou | Unmanned drone, robot system for delivering mail, goods, humanoid security, crisis negotiation, mobile payments, smart humanoid mailbox and wearable personal exoskeleton heavy load flying machine |
| US20150120057A1 (en) * | 2012-02-29 | 2015-04-30 | Irobot Corporation | Mobile Robot |
| US20150094883A1 (en) * | 2012-12-28 | 2015-04-02 | Google Inc. | Multi-part Navigation Process by an Unmanned Aerial Vehicle for Navigation |
| US20160236778A1 (en) * | 2014-07-08 | 2016-08-18 | Google Inc. | Bystander Interaction During Delivery from Aerial Vehicle |
Also Published As
| Publication number | Publication date |
|---|---|
| GB201907683D0 (en) | 2019-07-17 |
| CN110267720A (en) | 2019-09-20 |
| MX2019005847A (en) | 2019-09-26 |
| GB2570613A (en) | 2019-07-31 |
| US20180144645A1 (en) | 2018-05-24 |
| CA3044252A1 (en) | 2018-05-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11908184B2 (en) | Image capture with privacy protection | |
| US11932391B2 (en) | Wireless communication relay system using unmanned device and method therefor | |
| US20180144645A1 (en) | System and method for detecting humans by an unmanned autonomous vehicle | |
| US10498955B2 (en) | Commercial drone detection | |
| US20210239798A1 (en) | System, Method, and Computer Program Product for Automatically Configuring a Detection Device | |
| US20140140575A1 (en) | Image capture with privacy protection | |
| CN110888121B (en) | Target body detection method and device, and target body temperature detection method and device | |
| US20160292514A1 (en) | Monitoring system and method for queue | |
| US20240427010A1 (en) | Safety Device for Providing Output to an Individual Associated with a Hazardous Environment | |
| CN205679762U (en) | Dangerous goods detecting devices hidden by millimetre-wave radar | |
| US20220301303A1 (en) | Multispectral imaging for navigation systems and methods | |
| CN115167455A (en) | Autonomous mobile equipment control method and autonomous mobile equipment | |
| US11418980B2 (en) | Arrangement for, and method of, analyzing wireless local area network (WLAN) field coverage in a venue | |
| JP7006678B2 (en) | Mobile detection device, mobile detection method and mobile detection program | |
| EP3669209B1 (en) | Passive sense and avoid system | |
| CN117768607A (en) | Low-altitude flying object detection device, UAV detection and countermeasures device, method and system | |
| US11624660B1 (en) | Dynamic radiometric thermal imaging compensation | |
| EP3447527A1 (en) | Passive sense and avoid system | |
| KR20190142079A (en) | Mobile Base Station and System for Providing Services Using Mobile Base Station | |
| Kashihara et al. | Wi-SF: Aerial Wi-Fi sensing function for enhancing search and rescue operation | |
| KR101248150B1 (en) | Distance estimation system of concealed object using stereoscopic passive millimeter wave imaging and method thereof | |
| KR20240117181A (en) | Small infiltration drone identification system in short-wave infrared images | |
| GB2549195A (en) | Arrangement for, and method of, analyzing wireless local area network (WLAN) field coverage in a venue | |
| US10578726B2 (en) | Active sensing system and method of sensing with an active sensor system | |
| JP2023062219A (en) | Information processing method, information processing device and computer program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 17872048 Country of ref document: EP Kind code of ref document: A1 |
|
| ENP | Entry into the national phase |
Ref document number: 3044252 Country of ref document: CA |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| ENP | Entry into the national phase |
Ref document number: 201907683 Country of ref document: GB Kind code of ref document: A Free format text: PCT FILING DATE = 20171120 |
|
| 122 | Ep: pct application non-entry in european phase |
Ref document number: 17872048 Country of ref document: EP Kind code of ref document: A1 |