According to one embodiment, an information processing apparatus includes a processor. The processor is configured to acquire first received power on a route of a moving vehicle passing between a signal emission source and a radio wave shield, based on radio waves emitted from the signal emission source, in a state in which the radio wave shield is arranged at a first position, acquire second received power, which is a radio wave emitted from the signal emission source and measured on the route, in a state in which the radio wave shield is not arranged at the first position, and set a part of an area on the route as a target area based on an index related to fluctuation between the first received power and the second received power.

A computer-implemented method for driving assistance in a vehicle. The method includes generating, based on radar point sensor data of an environment of the vehicle, a three-dimensional occupancy grid map (3D OGM). The method includes generating, based on the radar point sensor data, a number of feature grid maps (FGMs). A respective feature dimension of each of the FGMs corresponds to a feature of the radar point sensor data. The method includes generating, based on the 3D OGM and the number of FGMs, a refined occupancy grid (OGM). The method includes providing the refined OGM for usage by an assistance system of the vehicle.

A drone which is an unmanned moving object according to an embodiment includes a flight controller that controls the driving of the drone, a first communication unit that communicates with an operation device that remotely controls the drone, and a second communication unit that receives unique information sent out from another moving object for identifying presence and/or a position of the other moving object.

A track fusion method for an unmanned surface vehicle includes: (a) obtaining perception information of the unmanned surface vehicle, where the perception information includes GPS data information and radar data information; (b) pre-processing the radar data information to obtain target radar information; (c) constructing a track correlation model; and performing track correlation between the GPS data information and the target radar information based on the track correlation model; and (d) constructing a fusion data weight allocation model; and subjecting between the GPS data information and the target radar information correlated therewith to track fusion based on the fusion data weight allocation model. This application further provides a track fusion device for unmanned surface vehicles.

An identification system comprising: a target detection unit detecting a plurality of objects; a radio wave irradiation part sequentially irradiating a radio wave to the plurality of the objects detected by the target detection unit; a radio wave detection unit provided in each of the plurality of objects, the radio wave detection unit detecting the radio wave irradiated by the radio wave irradiation part; and an identification unit identifying at least one of the objects among the plurality of the objects using time series data of the radio wave detected by the radio wave detection unit.

In various examples, one or more output channels of a deep neural network (DNN) may be used to determine assignments of obstacles to paths. To increase the accuracy of the DNN, the input to the DNN may include an input image, one or more representations of path locations, and/or one or more representations of obstacle locations. The system may thus repurpose previously computed informatione.g., obstacle locations, path locations, etc.from other operations of the system, and use them to generate more detailed inputs for the DNN to increase accuracy of the obstacle to path assignments. Once the output channels are computed using the DNN, computed bounding shapes for the objects may be compared to the outputs to determine the path assignments for each object. Additionally, a machine may perform control operations based at least on the path assignments.

A robotic emulation device includes a processor, memory and multimedia interfaces to capture a video signal from a target device, analyze it, and transmit manipulation control signals to the target device input by emulating a peripheral input device, wherein the manipulation control signals determine manipulation or selection of a target interface control associated with a first user interface encoded and transmitted in the video signal. Furthermore, the robotic emulation device may be connected via an embedded transceiver to at least one computer or computer tenant for relaying the captured video data for analysis, and based on the analysis, applying inferred manipulation semantics.

When a remotely controlled work machine loses a wireless connection on a work site, operation of the work machine should be terminated for safety purposes. However, if the work machine is moving when the wireless connection is lost, the work machine will continue moving for some time due to inertia. Accordingly, embodiments predict the signal quality of a wireless connection as a work machine approaches a new geographical location. When the predicted signal quality is low, the work machine may be proactively derated before it enters the geographical location. After entering the geographical location, if the actual signal quality is significantly better than the predicted signal quality, the work machine may be rerated. The predicted signal qualities may be determined based on a signal map that is independently maintained and updated by each work machine, so as to evolve over time with the work site and the work machine.

Provided is an aircraft landing guidance system including two transmitters that are disposed on a landing pad and transmit a first frequency signal and a second radio frequency signal continuously and a receiving unit that is provided on an aircraft and includes a first receiver receiving the first radio frequency signal and a second receiver receiving the second radio frequency signal, in which the aircraft is guided and controlled to land at a point of interest based on a relative angular position change and relative speed of the landing pad.

A control device that controls a mobile body that travels through unattended driving and the mobile body performs communication for controlling travel of the mobile body through the unattended driving and communication for inspecting the mobile body via an identical line. The control device includes a position acquisition unit that acquires position information indicating a current position of the mobile body, a storage unit storing first information indicating one or more inspections performed on the mobile body on a scheduled travel route of the mobile body and a point associated with each of the inspections where the inspection is performed on the travel route, and second information indicating a communication load in communication for the inspection and associated with the inspection, and a determination unit determining whether to cause the mobile body to travel through the unattended driving based on the position information, the first information, and the second information.