Example implementations described herein are directed to integration of far infrared cameras in a vehicle system to detect objects based on relative temperature of objects. Such implementations can improve accuracy when paired, for example, with classification systems that classify objects based on the shape of the object, as both the shape and relative temperature can be used to ensure that the classification is accurate. Further, example implementations can synchronize far infrared cameras with other sensor systems to determine distance, energy, and absolute temperature of an object, which can also be used to enhance classification. Such classifications can then be provided to an advanced driver assistance systems (ADAS), which can control the vehicle system in accordance with the object classification.

An artificial intelligence (AI) mobile robot and a method of controlling the same for learning an obstacle are configured to capture an image while traveling through an image acquirer, to store a plurality of captured image data, to determine an obstacle from image data, to set a response motion corresponding to the obstacle, and to operate the set response motion depending on the obstacle, and thus, the obstacle is recognized through the captured image data, the obstacle is easily determined by repeatedly learning an image, and the obstacle is determined before the obstacle is detected or from a time point of detecting the obstacle to perform an operation of a response motion, and even if the same detection signal is input when a plurality of different obstacles is detected, the obstacle is determined through the image and different operations are performed depending on the obstacle to respond to various obstacles, and accordingly, the obstacle is effectively avoided and an operation is performed depending on a type of the obstacle.

A vehicle control apparatus that controls movement of a vehicle in response to an instruction from a remote control terminal located outside the vehicle, the apparatus comprising: an obtaining unit configured to obtain an image captured by an image capturing unit configured to capture an image of a periphery of the vehicle; an operator detecting unit configured to detect an operator of the remote control terminal on the basis of the image obtained by the obtaining unit; a terminal detecting unit configured to detect a position of the remote control terminal relative to the vehicle; and a control unit configured to control, on the basis of a detection result from the operator detecting unit and a detection result from the terminal detecting unit, whether to permit or prohibit a remote control operation of the vehicle performed through the remote control terminal.

A mobile robot and a control method therefor, according to the present invention, are configured to determine whether a received signal is a pre-set signal and distinguish noise caused by overlapping of signals to control the operation of a sensor for detecting an obstacle according to an operation state of a main body such that transmission of a detection signal is limited, and thus has effects of the obstacle being easily detected by distinguishing each signal, the main body returning to a charging stand, and signal interference being minimized for a plurality of sensors using a signal of the same wavelength band.

A robot includes; a driving module, a communication module, and at least one processor configured to receive, a second docking guidance signal output from a second docking station; determine a first output time of the received second docking guidance signal, determine a second output time of a first docking guidance request signal to be transmitted based on the determined first output time to prevent the first docking guidance request signal from overlapping with the second docking guidance signal, and output the first docking guidance request signal, through the communication module, based on the determined second output time of the first docking guidance request signal, and in response to the outputting of the first docking guidance request signal, receive, a first docking guidance signal, docking the robot to the first docking station by driving the driving module in response to receiving the first docking guidance signal.

A nighttime delivery system is configured to provide delivery of packages during night hours, in low or no-light conditions using a multi-mode autonomous and remotely controllable delivery robot. The system involves the use of a baseline lighting system onboard the robot chassis, with variable light intensity from single flash and floodlighting, to thermal imaging using infrared cameras. The lighting system changes according to various environmental factors, and may utilize multi-mode lighting techniques to capture single-shot images with a flash light source to aid in the robot's perception when the vehicle is unable to navigate using infrared (IR) images.

Systems and methods for detecting glass for robots are disclosed herein. According to at least one non-limiting exemplary embodiment, a method for detecting glass objects using a LiDAR or light based time-of-flight (“ToF”) sensor is disclosed. According to at least one non-limiting exemplary embodiment, a method for detecting glass objects using an image sensor is disclosed. Both methods may be used in conjunction to enable a robot to quickly detect, verify, and map glass objects on a computer readable map.

A method for adaptively operating a cleaning robot based on height difference between floors and the cleaning robot are provided, and according to an embodiment of the present disclosure, the cleaning robot that adaptively operates based on the height difference between the floors includes a central controller that controls a height adjuster that controls a height of a floor cleaner based on height information related to a space stored in a map storage and height information sensed by a sensor.

An exemplary embodiment of the present disclosure provides a method, an apparatus, a system, an electronic device and a storage medium for robot navigation. The robot navigation system includes: a first infrared receiving unit, a second infrared receiving unit, a distance measuring unit, and a processing unit, where the first infrared receiving unit and the second infrared receiving unit are disposed on a robot to receive a first infrared signal and a second infrared signal from an infrared transmission unit respectively; the distance measuring unit is disposed on the robot to obtain a distance signal indicating a distance between the robot and the target device; the processing unit is configured to: obtain the first infrared signal, the second infrared signal and the distance signal, control a moving direction of the robot based on the first infrared signal and the second infrared signal, and control the robot to move to the target device in response to determining that the robot enters a docking scope based on the distance signal. In the embodiments of the present disclosure, the costs of the navigation system are reduced with the accuracy improved.

In various examples, a current claimed set of points representative of a volume in an environment occupied by a vehicle at a time may be determined. A vehicle-occupied trajectory and at least one object-occupied trajectory may be generated at the time. An intersection between the vehicle-occupied trajectory and an object-occupied trajectory may be determined based at least in part on comparing the vehicle-occupied trajectory to the object-occupied trajectory. Based on the intersection, the vehicle may then execute the first safety procedure or an alternative procedure that, when implemented by the vehicle when the object implements the second safety procedure, is determined to have a lesser likelihood of incurring a collision between the vehicle and the object than the first safety procedure.