A path planning device includes: data acquisition means for acquiring position data of an obstacle; storage means for storing the position data of the obstacle; and path setting means for setting, based on an environmental map, the acquired position data of the obstacle and the position data of the obstacle stored in the storage means, a moving path to a target position, and regularly updating the moving path. The path setting means sets, when the path setting means determines that the acquired obstacle is positioned on a first moving path to the target position after the first moving path is set, a second moving path in which there is no obstacle on a moving path. The storage means stores the position data of the obstacle on the first moving path when the moving load along the second moving path is larger than the moving load along the first moving path.

Embodiments of the present disclosure disclose a method and apparatus for outputting obstacle information. A specific embodiment of the method comprises: determining a candidate direction information set of a target obstacle point cloud; determining, for each piece of candidate direction information in the candidate direction information set, a target value of the target obstacle point cloud in a direction indicated by the candidate direction information based on the target obstacle point cloud and a smallest circumscribing rectangle of the target obstacle point cloud in the direction indicated by the candidate direction information; defining candidate direction information having a minimum target value in the candidate direction information set as direction information corresponding to the target obstacle cloud point; and outputting the direction information corresponding to the target obstacle cloud point, thereby improving the abundance of content of outputted obstacle information.

Driver and pedestrian safety can be aided by systems and methods to provide identification and classification of objects in a vehicle travel path. Information about classified objects can be shared with a human driver to inform the driver about potentially hazardous conditions, or the information can be interpreted automatically by an operating system of the vehicle. In an example, a camera coupled to a vehicle can receive images from an image sensor. A computer system can use machine learning and neural network-based processing to identify an object present in the images and determine whether the object is a pedestrian. In an example, the computer system can process information from a region of interest in the images that comprises less than an entire field of view in the images.

A system and method for online real-time multi-object tracking is disclosed. A particular embodiment can be configured to: receive image frame data from at least one camera associated with an autonomous vehicle; generate similarity data corresponding to a similarity between object data in a previous image frame compared with object detection results from a current image frame; use the similarity data to generate data association results corresponding to a best matching between the object data in the previous image frame and the object detection results from the current image frame; cause state transitions in finite state machines for each object according to the data association results; and provide as an output object tracking output data corresponding to the states of the finite state machines for each object.

An objective of the present invention is, in a stereo camera device, to determine an accurate image position in a direction of progress to detect at an early stage an obstacle or a preceding vehicle on a road. Provided is a stereo camera device for measuring the distance to a solid object from images photographed with a plurality of cameras, said device characterized by: a wide-angle image cropping part for cropping a portion of the images; a distance image cropping part for cropping and enlarging a portion of the images; a road shape determination part for determining a road shape, including slope information, of a road being traveled; and determining, on the basis of the road shape in a prescribed distance, which has been derived with the road shape determination part, the cropping position and/or range of the distance image cropping part.

Methods and systems according to one or more examples are provided for avoiding foreign object strikes on rotorcraft vehicles. In one example, a vehicle comprises a rotor comprising a rotor blade, a first sensor configured to provide first sensor information associated with an object proximate the vehicle, and a second sensor configured to provide second sensor information associated with the rotor. The vehicle further comprises a processor coupled to the first sensor and the second sensor configured to selectively control the rotor to minimize damage to the vehicle by the object based on the first and second sensor information.

An object detection device includes a processor configured to calculate, for each of a plurality of regions in a detection range of the sensor represented in the newest sensor signal among a plurality of sensor signals in time-series acquired by a sensor, a confidence indicating a degree of certainty that an object to be detected is represented in the region; track a first object which has been detected, to detect, in the newest sensor signal, a passed region through which the first object has passed; control, for each of the plurality of regions in the newest sensor signal, a confidence threshold according to whether or not the region is included in the passed region, and detect a second object in a region, among the plurality of regions, with respect to which the confidence for the second object is equal to or higher than the confidence threshold.

The present invention discloses a grid map obstacle detection method fusing probability and height information, and belongs to the field of image processing and computer vision. A high-performance computing platform is constructed by using a GPU, and a high-performance solving algorithm is constructed to obtain obstacle information in a map. The system is easy to construct, the program is simple, and is easy to implement. The positions of obstacles are acquired in a multi-layer grid map by fusing probability and height information, so the robustness is high and the precision is high.

A system is comprised of one or more processors coupled to memory. The one or more processors are configured to receive image data based on an image captured using a camera of a vehicle and to utilize the image data as a basis of an input to a trained machine learning model to at least in part identify a distance of an object from the vehicle. The trained machine learning model has been trained using a training image and a correlated output of an emitting distance sensor.

The disclosure provides a method for operating an autonomous vehicle. To operate the autonomous vehicle, a plurality of lane segments that are in an environment of the autonomous vehicle is determined and a first object and a second object in the environment are detected. A first position for the first object is determined in relation to the plurality of lane segments, and particular lane segments that are occluded by the first object are determined using the first position. According to the occluded lane segments, a reaction time is determined for the second object and a driving instruction for the autonomous vehicle is determined according to the reaction time. The autonomous vehicle is then operated based on the driving instruction.