Member Info for johnchucka

SYSTEMS AND METHODS FOR ENHANCED DISTANCE ESTIMATION BY A MONO-CAMERA USING RADAR AND MOTION DATA
Systems and methods for depth estimation of images from a mono-camera by use of radar data by: receiving, a plurality of input 2-D images from the mono-camera; generating, by the processing unit, an estimated depth image by supervised training of an image estimation model; generating, by the processing unit, a synthetic image from a first input image and a second input image from the mono-camera by applying an estimated transform pose; comparing, by the processing unit, an estimated three-dimensional (3-D) point cloud to radar data by applying another estimated transform pose to a 3-D point cloud wherein the 3-D point cloud is estimated from a depth image by supervised training of the image estimation model to radar distance and radar doppler measurement; correcting a depth estimation of the estimated depth image by losses derived from differences: of the synthetic image and original images; of an estimated depth image and a measured radar distance; and of an estimated doppler information and measured radar doppler information.

[0027] In various exemplary embodiments, the present disclosure describes systems and methods for training a model for generating high resolution depth images that does not rely on Structure from Motion (SfM) techniques that are inefficient because SfM techniques require significant processing steps of large (x or y) rotation, large field of view and depth variation and continuous camera calibrations.
https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2020167941A1&KC=A1&FT=D&ND=3&date=20200528&DB=&locale=en_EP#

SEE.
SYSTEM AND METHOD FOR IDENTIFYING A CAMERA POSE OF A FORWARD FACING CAMERA IN A VEHICLE
A method includes capturing images of a vehicle driver's face from a driver facing camera and images of a forward road scene from a forward facing camera. The images are analyzed to derive gaze direction data in a vehicle frame of reference. The gaze direction data are statistically collated to determine a frequency distribution of gaze angles. One or more peaks in the frequency distribution are identified and associated with corresponding reference points in the images to determine one or more reference gaze positions in the vehicle frame of reference. The one or more reference gaze positions are correlated with a position of the reference points in a forward facing camera frame of reference to to determine a camera pose of a forward facing camera in the vehicle frame of reference.

GM
METHODS AND SYSTEMS FOR PROCESSING DRIVER ATTENTION DATA
Methods and systems are provided for processing attention data. In one embodiment, a method includes: receiving, by a processor, object data associated with at least one object of an exterior environment of the vehicle; receiving upcoming behavior data determined from a planned route of the vehicle; receiving gaze data sensed from an occupant of the vehicle; processing, by the processor, the object data, the upcoming behavior data, and the gaze data to determine an attention score associated with an attention of the occupant of the vehicle; and selectively generating, by the processor, signalsto at least one of notify the occupant and control the vehicle based on the attention score.
https://worldwide.espacenet.com/publicationDetails/biblio?II=13&ND=3&adjacent=true&locale=en_EP&FT=D&date=20191029&CC=CN&NR=110386146A&KC=A#

Qualcomm
EARLY FUSION OF CAMERA AND RADAR FRAMES
Disclosed are techniques for fusing camera and radar frames to perform object detection in one or more spatial domains. In an aspect, an on-board computer of a host vehicle receives, from a camera sensor of the host vehicle, a plurality of camera frames, receives, from a radar sensor of the host vehicle, a plurality of radar frames, performs a camera feature extraction process on a first camera frame of the plurality of camera frames to generate a first camera feature map, performs a radar feature extraction process on a first radar frame of the plurality of radar frames to generate a first radar feature map, converts the first camera feature map and/or the first radar feature map to a common spatial domain, and concatenates the first radar feature map and the first camera feature map to generate a first concatenated feature map in the common spatial domain.
https://worldwide.espacenet.com/publicationDetails/description?CC=US&NR=2020175315A1&KC=A1&FT=D&ND=3&date=20200604&DB=&locale=en_EP#

TLS,
Interesting to note same author named in SYSTEMS AND METHODS FOR OBJECT LOCATION patent and includes;

[0028] FIG. 1 is a block diagram illustrating one example of an apparatus 102 in which systems and methods for object location may be implemented. For instance, the apparatus 102 may be configured to locate one or more objects in an environment based on image data. Examples of the apparatus 102 include vehicles, autonomous vehicles, cameras, video camcorders, digital cameras, smart phones, computers (e.g., integrated computers, on-board computers, laptop computers, etc.), tablet devices, personal cameras, action cameras, surveillance cameras, mounted cameras, connected cameras, robots, aircraft, drones, unmanned aerial vehicles (UAVs), healthcare equipment, gaming consoles, personal digital assistants (PDAs), etc. For instance, the apparatus 102 may be an autonomous vehicle, a self-driving vehicle, etc., and/or may include an Advanced Driver Assistance System (ADAS). The apparatus 102 may include one or more components or elements. One or more of the components or elements may be implemented in hardware (e.g., circuitry, an application specific integrated circuit (ASIC), etc.), implemented in a combination of hardware and software (e.g., a processor with instructions), and/or may be implemented in firmware.

[0031] In some configurations, the apparatus 102 may present a user interface 134 on the display 132. For example, the user interface 134 may enable a user to interact with the apparatus 102. In some configurations, the display 132 may be a touchscreen that receives input from physical touch (by a finger, stylus, or other tool, for example). Additionally or alternatively, the apparatus 102 may include or be coupled to another input interface. For example, the apparatus 102 may include a camera facing a user and may detect user gestures (e.g., hand gestures, arm gestures, eye tracking, eyelid blink, etc.). In another example, the apparatus 102 may be coupled to a mouse and may detect a mouse click. In some configurations, one or more of the images described herein may be presented on the display 132 and/or user interface 134. In some configurations, the user interface 134 may enable a user to indicate preferences (e.g., view settings) and/or interact with the view.
https://worldwide.espacenet.com/publicationDetails/description?CC=US&NR=2018192035A1&KC=A1&FT=D&ND=3&date=20180705&DB=&locale=en_EP#

Perhaps related to #3 and potentially to inward /outward camera fusion technology advancements.

Processing Sensor Information for Object Detection Qualcomm #4
Methods of processing vehicle sensor information for object detection may include capturing generating a feature map based on captured sensor information, associating with each pixel of the feature map a prior box having a set of two or more width priors and a set of two or more height priors, determining a confidence value of each height prior and each width prior, outputting an indication of a detected object based on a highest confidence height prior and a highest confidence width prior, and performing a vehicle operation based on the output indication of a detected object. Embodiments may include determining for each pixel of the feature map one or more prior boxes having a center value, a size value, and a set of orientation priors, determining a confidence value for each orientation prior, and outputting an indication of the orientation of a detected object based on the highest confidence orientation.
https://worldwide.espacenet.com/publicationDetails/description?CC=US&NR=2020175286A1&KC=A1&FT=D&ND=3&date=20200604&DB=&locale=en_EP#

TLS,
I am interested in your observations as to the possibility that this Qualcomm patent potentially incorporates/fuses SEE patent SYSTEM AND METHOD FOR IDENTIFYING A CAMERA POSE OF A FORWARD FACING CAMERA IN A VEHICLE with radar.

EARLY FUSION OF CAMERA AND RADAR FRAMES
Disclosed are techniques for fusing camera and radar frames to perform object detection in one or more spatial domains. In an aspect, an on-board computer of a host vehicle receives, from a camera sensor of the host vehicle, a plurality of camera frames, receives, from a radar sensor of the host vehicle, a plurality of radar frames, performs a camera feature extraction process on a first camera frame of the plurality of camera frames to generate a first camera feature map, performs a radar feature extraction process on a first radar frame of the plurality of radar frames to generate a first radar feature map, converts the first camera feature map and/or the first radar feature map to a common spatial domain, and concatenates the first radar feature map and the first camera feature map to generate a first concatenated feature map in the common spatial domain.
https://worldwide.espacenet.com/publicationDetails/description?CC=US&NR=2020175315A1&KC=A1&FT=D&ND=3&date=20200604&DB=&locale=en_EP#

DEPTH IMAGE BASED FACE ANTI-SPOOFING
Methods, systems, and devices for image processing are described. The method may include identifying a face in a first image based on identifying one or more biometric features of the face, determining an angular direction of one or more pixels of the identified face, identifying an anchor point on the identified face, sorting each of one or more pixels of the identified face into one of a set of pixel bins based on a combination of the determined angular direction of the pixel and a distance between the pixel and the identified anchor point, and outputting an indication of authenticity associated with the face based on a number of pixels in each bin.

The present techniques introduce depth feature representation referred to as an Angular Spherical Face Representation (ASFR), a feature descriptor to represent the face or object geometry; a machine learning algorithms (e.g. deep neural network (DNN)) that uses ASFR as input to determine whether an image of a face is authentic; a face normalization method to avert sensor deficiencies; and a data augmentation process to increase the amount of data used in training. The present techniques validate the effectiveness of ASFR with various machine leaning algorithms (e.g., DNN anti-spoofing). It is noted that although convolutional neural network (CNN) is a viable machine learning solution to learn robust features of a face in a depth image, CNN requires a significantly more amount of data for training than DNN. Machine learning of the present techniques may implement a pre-trained network on an image database (e.g., Image-Net, AlexNet, GoogleNet, etc.) and may include fine tuning the pre-trained network for anti-spoofing. In one example, refining the pre-trained may include mapping the ASFR feature map as a heat map image of a certain size. In some cases, pre-Attorney trained networks may be pre-trained on images and heatmaps and thus may be implemented and refined for the present techniques.

The present techniques provide depth image based face anti-spoofing by receiving an input depth image; normalizing the input depth image to a frontal pose; generating an ASFR by computing the angular direction of each pixel and its distance to an anchor point based on a normalized input depth image; using the ASFR as input to a machine learning model; and determining whether the input depth image is a fake image based on an output of the machine learning model. In some cases, normalizing the input depth image may include positioning the image on an XY graph, aligning a first vector from the left eye to the right eye with the X-axis, and adjusting the image so that the angle between a second vector from the center between the left eye and the right eye to an anchor point (e.g., identified nose tip) and the Y-axis is 45 degrees.
https://tinyurl.com/y8cwfwtx
https://patents.justia.com/patent/20200175260

LOOK-ASIDE DETERMINATION DEVICE
To provide a look-aside determination device that can appropriately determine that a driver is looking aside even when the driver is gazing at a gaze target provided in front of a driver's seat.SOLUTION: A look-aside determination device 1 comprises: a driver information acquisition unit 11 for acquiring a face direction or a line-of-sight direction of a driver; a gaze determination unit 12 that determines whether or not a driver is in a vehicle gaze state where the driver is gazing at a gaze target G provided in front of a driver's seat of a vehicle based on the face direction or the line-of-sight direction of the driver; an external environment recognizing unit 13 for recognizing an external environment around the vehicle; a visual recognition target determination unit 14 that determines whether it is an environment in which a visual recognition target that induces the face direction or the line-of-sight direction of the driver in a direction other than tha gaze target exists outside the vehicle based on the external environment; and a look-aside determination unit 15 that determines that the driver is looking aside when it is determined that the driver is in the vehicle gaze state if it is determined that it is the environment in which the visual recognition target exists outside the vehicle.SELECTED DRAWING: Figure 1

The aside-view determination device according to an aspect of the present disclosure is a aside-view determination device that determines that a driver of a vehicle is looking away, and a driver information acquisition unit that acquires a face direction or a line-of-sight direction of the driver. Whether or not the driver is in the in-vehicle gaze state gazing at the gaze target provided in front of the driver's seat of the vehicle based on the driver's face direction or gaze direction acquired by the driver information acquisition unit Gaze determination unit that determines the external environment recognition unit that recognizes the external environment around the vehicle, based on the external environment recognized by the external environment recognition unit, the driver's face direction or gaze direction other than the gaze target When the visual target to be attracted in the direction is the visual target determination unit that determines whether the visual target exists outside the vehicle, and the visual target determination unit determines that the visual target exists outside the vehicle. In the above, when the gaze determination unit determines that the driver is in the in-vehicle gaze state, the look-around determination unit determines that the driver is looking away.
https://tinyurl.com/ydxgvk4c

METHOD AND DEVICE IN A VEHICLE FOR EVALUATING AND STORING DATA
A device and a method in a vehicle which is controlled in autonomous or highly-automated driving mode without intervention of the driver or in a manual driving mode by the driver of the vehicle, the device evaluating and storing data, and the device including a memory unit, in which data are recorded which at least include pieces of information about whether the autonomous or highly-automated driving mode was active or the manual driving mode was active at a collision point in time or up to shortly before the collision point in time. Sensor signals from driver-actuatable operating elements and from collision recognition units are evaluated.
https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2020175787A1&KC=A1&FT=D&ND=3&date=20200604&DB=&locale=en_EP#

3D CLUSTER AND METHOD OF CALIBRATING THE SAME
A 3D cluster and a method of calibrating the 3D cluster are disclosed. The method of calibrating the 3D cluster, which includes a 3D display panel configured to display images for a left eye and images for a right eye of a driver, and which includes a barrier configured to divide the images for the left eye and the images for the right eye to be transmitted to each of the left eye and the right eye of the driver. The method includes graphically displaying, by a controller, a graphical element representing an arrangement state of the barrier through the 3D display panel and guiding, by the controller, the driver to change the arrangement state of the barrier through adjustment of the graphical element.
https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2020174267A1&KC=A1&FT=D&ND=3&date=20200604&DB=&locale=en_EP#
https://patents.justia.com/patent/20200174267
Drawings
http://www.freepatentsonline.com/20200174267.pdf

DISABLING AUGMENTED REALITY (AR) DEVICES AT SPEED
Systems, apparatus and methods for limiting information on an augmented reality (AR) display based on various speeds of an AR device are presented. Often information forms a distraction when the wearer is driving, running or even walking. Therefore, the described systems, devices and methods aim to limit information displayed on an AR display based on three or more levels movement (e.g., stationary, walking, driving) such that the wearer is less distracted when higher levels of concentration are needed for real world activities.
https://worldwide.espacenet.com/publicationDetails/biblio?II=0&ND=3&adjacent=true&locale=en_EP&FT=D&date=20200604&CC=US&NR=2020175769A1&KC=A1#

Major Accident Report 2020
https://ntarc.nationaltransportinsurance.com.au/#introduction

These two recent Honda patents also may have relevance to the Qualcomm/ Honda relationship.
https://www.trustedreviews.com/news/qualcomm-packing-snapdragon-tech-honda-jaguar-land-rover-vehicles-3367900

LINE-OF-SIGHT DETECTION APPARATUS, COMPUTER READABLE STORAGE MEDIUM, AND LINE-OF-SIGHT DETECTION METHOD
A line-of-sight detection apparatus includes a first direction determining section that determines a first direction that is a direction of a line of sight of a first eye of a subject; a second direction determining section that determines a second direction that is a direction of a line of sight of a second eye of the subject; an assuming section that assumes a gaze direction of the subject based on at least one of (i) a manipulation by the subject of a device provided with a line-of-sight measurement apparatus that measures a line of sight of the subject, (ii) a state of the device, and (iii) an orientation of a face of the subject; and a first judging section that compares the assumed gaze direction, the first direction, and the second direction, and judges which of the first eye and the second eye is a dominant eye.
https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2020150759A1&KC=A1&FT=D&ND=3&date=20200514&DB=&locale=en_EP#

CONTROL APPARATUS, CONTROL METHOD, AGENT APPARATUS, AND COMPUTER READABLE STORAGE MEDIUM
A control apparatus controls an agent apparatus functioning as a user interface of a request processing apparatus that acquires a request indicated by at least one of a voice and a gesture of a user and performs a process corresponding to the request. The control apparatus includes a gaze point specifying section specifying a gaze point of the user, and a face control section controlling an orientation of a face or line of sight of an agent used to transmit information to the user. The face control section controls the orientation of the face or line of sight of the agent such that the face or line of sight of the agent becomes oriented toward the user, if the gaze point is positioned at (i) a portion of the agent or (ii) a portion of an image output section that displays or projects an image of the agent.
https://worldwide.espacenet.com/publicationDetails/biblio?II=5&ND=3&adjacent=true&locale=en_EP&FT=D&date=20200507&CC=US&NR=2020143185A1&KC=A1#

Qualcomm Collaborates with 15 Global Operators to Deliver XR Viewers.

Qualcomm Technologies, Inc., a subsidiary of Qualcomm Incorporated, today at Augmented World Expo (AWE), celebrates the milestone of partnering with global operators, smartphone OEMs and XR viewer manufacturers to deliver XR viewers to consumers and enterprises within the next year. Since Qualcomm Technologies’ device category introduction of XR viewers tethered to 5G smartphones, fifteen global operators including China Mobile, China Telecom, China Unicom, Deutsche Telekom, EE, KDDI, KT, LG Uplus, NTT DOCOMO, Orange, SK Telecom, SoftBank, Telefonica, Verizon and Vodafone have shared plans to sample and commercialize XR viewers to provide immersive, never-before-experiences over 5G.
https://www.qualcomm.com/news/releases/2020/05/26/qualcomm-collaborates-15-global-operators-deliver-xr-viewers

S2020 reminded us of Semicast Speculation recently;

'Back in Jan Colin Barnden clearly thought the Qualcomm deal was bigger than just auto.
"Semicast Research@semicast_res
Jan 10
THIS IS SPECULATION: Qualcomm takes exclusive license for eye gaze tracking in smartphones. Gives competitive advantage over Apple and Samsung.
@seeingmachines is funded to profit with a steady royalty stream."

Replacement
Correct me if I'm wrong TLS but I think your referring to SEE patent ;
SYSTEM AND METHOD FOR IDENTIFYING A CAMERA POSE OF A FORWARD FACING CAMERA IN A VEHICLE
https://worldwide.espacenet.com/publicationDetails/biblio?II=2&ND=3&adjacent=true&locale=en_EP&FT=D&date=20190829&CC=US&NR=2019266751A1&KC=A1#
which is referenced in the patent commentary below in relation to over lapping or conflicting claims in the Global dossier of the GM patent below where the above patent is mentioned as TLS pointed out.
https://register.epo.org/documentView?number=US.201816201618.A&documentId=1-12-US++162016180BP1+

Correct me if I'm wrong TLS but I think your referring to SEE patent ;
SYSTEM AND METHOD FOR IDENTIFYING A CAMERA POSE OF A FORWARD FACING CAMERA IN A VEHICLE
https://worldwide.espacenet.com/publicationDetails/biblio?II=2&ND=3&adjacent=true&locale=en_EP&FT=D&date=20190829&CC=US&NR=2019266751A1&KC=A1#
where reference is made to over lapping or conflicting claims in the Global dossier of the GM patent below where the above patent is mentioned as TLS pointed out.
https://register.epo.org/documentView?number=US.201816201618.A&documentId=1-12-US++162016180BP1+

MOVEMENT TRACKING OF OPERATOR-FACING CAMERAS
Systems and methods for optimizing operator-state detection including tracking position of an operator-facing camera are described. Systems and methods include receiving a first image captured by an operator-facing camera, detecting a first position of the operator-facing camera with respect to the calibration object, ascertaining the first position with respect to at least one fiducial marker within a passenger compartment of a vehicle, capturing, via controller, a second image using the operator-facing camera, determining the second image is captured by the operator-facing camera from a second position with respect to the at least one fiducial marker, and analyzing, based on determining the second image is captured by the operator-facing camera from the second position, the second image to identify facial features of the operator. The receiving, detecting, ascertaining, determining, and analyzing are performed via a controller. The first image includes a calibration object disposed at a predetermined location.

Beneficially, systems and methods in accordance with the present disclosure may optimize functioning of an operator monitoring system. Such optimizations may include optimizing the identification of facial features, reducing processing time required to identify facial features, reducing data storage requirements for analysis of facial features, and/or reducing misidentification of an operator's state. Further, systems and methods in accordance with the present disclosure may optimize vehicle function through accurate assessment of an operator state. Such optimized vehicle function may include prolonged operation in autonomous and semi-autonomous modes to thereby reduce operator interventions with the vehicle and reduced handoffs between autonomous and non-autonomous modes. According to aspects of the present disclosure, these and other benefits are accomplished by systems and methods of tracking spatial placement of an operator-facing camera that is movable, for example, during adjustments to optimize visibility and comfort of an operator.

Claims
1. A method comprising:
receiving, via a controller, a first image captured by an operator-facing camera, the first image including a calibration object disposed at a predetermined location, the operator-facing camera being movable within a passenger compartment of a vehicle;
https://worldwide.espacenet.com/publicationDetails/biblio?II=14&ND=3&adjacent=true&locale=en_EP&FT=D&date=20200528&CC=US&NR=2020167951A1&KC=A1#
https://patents.justia.com/patent/20200167951
Drawings
http://www.freepatentsonline.com/20200167951.pdf

Yeah Elon I've always been glad Elevators have buttons to stop them crashing into each other when they jump shafts.

Peripheral vision in human-machine interface
The invention relates to peripheral vision in a human-machine interface. A computer-implemented method for managing a graphical human-machine interface, includes the steps of receiving information relating to the position of the eyes and the gaze direction of a user at the interface; receiving physiological information of the user; determining a level of cognitive load on the basis of the receivedphysiological information; adjusting the display of the interface on the basis of the gaze direction and/or of the determined level of cognitive load. Some developments describe the management of thedisplay zones (foveal zone and peripheral zones), the selection of one or more displays, the management of the distance from the message display to the current gaze location, the management of the criticality of the messages, various graphical techniques for attracting attention, the management of the flight context in the avionic case, the management of visual density, etc. Some system aspects are described (virtual and/or augmented reality).
https://worldwide.espacenet.com/publicationDetails/biblio?CC=CN&NR=110155349A&KC=A&FT=D&ND=3&date=20190823&DB=&locale=en_EP#
http://translationportal.epo.org/emtp/translate/?ACTION=description-retrieval&COUNTRY=CN&ENGINE=google&FORMAT=docdb&KIND=A&LOCALE=en_EP&NUMBER=110155349&OPS=ops.epo.org/3.2&SRCLANG=zh&TRGLANG=en

Driver Attention -Handover- Transition. (+Ford) (+Volvo)

TOYOTA MOTOR EUROPE [BE]; UCL BUSINESS PLC 2020-05-07
CONTROL DEVICE, SYSTEM AND METHOD FOR DETERMINING THE PERCEPTUAL LOAD OF A VISUAL AND DYNAMIC DRIVING SCENE

HYUNDAI MOTOR CO LTD [KR]; KIA MOTORS CORP [KR] 2020-05-14
DRIVER DISTRACTION WARNING CONTROL APPARATUS AND METHOD

Bosch 2020-02-06
METHOD AND DEVICE FOR ASSISTING A DRIVER DURING THE DEACTIVATION OF A HIGHLY AUTOMATED DRIVING MODE OF A VEHICLE .

Toyota 2020-05-14
SYSTEMS AND METHODS FOR TRANSITIONING A VEHICLE FROM AN AUTONOMOUS DRIVING MODE TO A MANUAL DRIVING MODE

Bosch 2020-04-30
METHOD AND DEVICE FOR ADAPTING A POSITION OF A SEAT DEVICE OF A VEHICLE DURING AND/OR PRIOR TO A SWITCHOVER OF THE VEHICLE FROM AN AUTOMATED DRIVING MODE TO A MANUAL DRIVING MODE

GM GLOBAL TECH 2020-05-07
SPATIAL AND TEMPORAL ATTENTION-BASED DEEP REINFORCEMENT LEARNING OF HIERARCHICAL LANE-CHANGE POLICIES FOR CONTROLLING AN AUTONOMOUS VEHICLE

Addition#1
FORD GLOBAL TECH 2020-05-14
APPARATUS AND METHOD FOR DETERMINING AN ATTENTION REQUIREMENT LEVEL OF A DRIVER OF A VEHICLE
https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2020148225A1&KC=A1&FT=D&ND=3&date=20200514&DB=&locale=en_EP#

Addition#2
Volvo car Corp 2020-04-23
SYSTEM AND METHOD FOR DETECTING AND/OR PREVENTING AUTOMATION EXPECTATION MISMATCH IN VEHICLE
https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2020122745A1&KC=A1&FT=D&ND=3&date=20200423&DB=&locale=en_EP#

CONTROL OF ROBOTIC VEHICLES BASED ON ATTENTION LEVEL OF OPERATOR.
Embodiments include devices and methods for controlling a robotic vehicle, the method including detecting, by one or more processors, a distraction event while an operator is controlling the robotic vehicle and automatically controlling the robotic vehicle in response to detecting the distraction event.

BACKGROUND
[0001] Robotic vehicles are increasingly used for a wide range of applications, including personal, commercial and government applications. Robotic vehicles are typically unmanned and may be operated by remote commands from an operator or in an autonomous mode where the robotic vehicle controls its own operations. In the case where the robotic vehicle is being controlled by remote commands from the operator, the operator is relied on to stay apprised of the conditions surrounding the robotic vehicle and to provide commands to operate the robotic vehicle in a safe and efficient manner.

[0002] There are various situations that may cause safety or privacy concerns, or other issues if a robotic vehicle is not controlled properly. For example, if the right commands are not received from the operator while the robotic vehicle is being controlled by the operator, the robotic vehicle may operate in a manner that may lead to collisions, flying into restricted areas, or other such situations that may cause concern.

[0003] In addition, robotic vehicles have limited resources, such as battery life. Because of these limited resources, it is important that while the resources are in use, the robotic vehicle is controlled in an efficient manner to make sure the resources are used in an optimal way. This can ensure that the robotic vehicle is able to complete the desired tasks, and provide an optimal result and/or user experience.

[0004] For at least these reasons, it is important that the operator of the robotic vehicle is alert and provides the right commands to the robotic vehicle during its flight. However, it is possible for an operator to become distracted during operation of the robotic vehicle. Therefore, it is desirable to address the possibility of distractions of the operator to avoid safety and privacy concerns, as well as any inefficient use of the robotic vehicle limited resources.
https://worldwide.espacenet.com/publicationDetails/description?CC=US&NR=2019310630A1&KC=A1&FT=D&ND=3&date=20191010&DB=&locale=en_EP#