Sz Dji Technology Co., Ltd.

Tencent Technology (shenzhen) Company Limited

Guangzhou Automobile Group Co., Ltd.

Zte Corporation

Huawei Digital Power Technologies Co., Ltd.

Shenzhen Zhuoyu Technology Co., Ltd.

Shenzhen Chipscreen Biosciences Co., Ltd.

You Zhou

Cong Zhao

Jiaqi Yan

Xuyang Feng

Yi Xie

Jie Qian

Ketan Tang

Guyue Zhou

Zhenyu Zhu

Jia Qu

Jie Liu

Honghui Zhang

Zhe Liu

Dan Yang

Rui Li

Bing Li

Xiang Zhang

Lei Han

Junfeng Yu

Tao Zhao

Mingyu Wang

Xiao Liang Hu

Bo Huang

Zisheng Cao

Ang Liu

Kai Xin

Yun Yu

Linchao Bao

Zhuo Guo

Wen Xu

Shunnian Li

Yanan Wang

Gang Xu

Shaojie Shen

Litian Zhang

Xianping Lu

Peiliang Li

Xiaoming Ling

Minjian Pang

Xuewu Liu

Fenfen Ma

Changning Tai

Zhaoliang Peng

Pan Hu

Song Shan

Jiexi Du

Shi Shu

Baisong Wei

Jianzhao Cai

Tianli Xie

Ge Lei

Wenlin Yu

Lixue Chen

Changchun Ye

Jiajing Guan

Anwei Zhang

Xian Wang

Zhiqiang Ning

Zhangping Shao

Bing Wu

Lijun Xin

Jinsong Li

Chenglin Mao

Deng-Feng Hu

Zhiyuan Wu

Desi Pan

Hong-Ju Li

Shigang Wang

Dongwei Liang

Hualiang Feng

Yushi Long

A converter circuit is configured to output a first reactive current to a power grid when a voltage value of an output port of the converter circuit decreases from a first working voltage value to a second working voltage value. The drive control circuit is configured to: in a process in which the converter circuit outputs the first reactive current to the power grid, when it is detected that the voltage value of the output port of the converter circuit increases to a third working voltage value and the third working voltage value is greater than or equal to a first recovery voltage value, control the converter circuit to output a second reactive current to the power grid, to recover the voltage value of the output port of the converter circuit to the first working voltage value.

Power supply system and current conversion method

A gimbal pose correction method includes obtaining a first pose of a gimbal based on a sensor arranged at a vertical compensation device configured to be coupled to the gimbal and compensate for movement of the gimbal in a vertical direction, obtaining a second pose of the vertical compensation device based on a vision device arranged at the vertical compensation device, and correcting the first pose according to the second pose.

Gimbal pose correction method and device

The present disclosure provides a device for controlling a mobile platform. The device includes a processor; and a memory storing program instructions that, when being executed by the processor, cause the processor to receive an instruction to enter a point of interest (POI) circle mode; and enter the POI circle mode, the POI circle mode including a target determination phase, a target estimation phase, and a circling phase in sequence. The mobile platform determines a circling target during the target determination phase. The mobile platform detects a position of the circling target during the target estimation phase. The mobile platform circles the circling target based on the position of the circling target during the circling phase.

Method and device for controlling mobile platform

Identifying interfering features in the detection of an environment adjacent to a mobile platform, and associated systems and methods are disclosed herein. A representative method can include identifying candidate regions from a color image obtained by a color vision sensor carried by a mobile platform, filtering out a first region subset of regions based, at least in part, on non-image data obtained by a second sensor carried by the mobile platform, determining a second subset of regions as corresponding to an interfering feature based, at least in part, on color information, and performing environment detection based, at least in part, on the second subset of regions. Furthermore, the method can comprise transforming data corresponding to the subset of regions to integrate with non-color environment data obtained from another sensor carried by the mobile platform.

Sky determination in environment detection for mobile platforms, and associated systems and methods

Automatic terrain evaluation of landing surfaces, and associated systems and methods are disclosed herein. A representative method includes receiving a request to land a movable object and, in response to the request, identifying a target landing area on a landing surface based on at least one image of the landing surface obtained by the movable object. The method can further include directing the movable object to land at the target landing area.

Automatic terrain evaluation of landing surfaces, and associated systems and methods

A method for controlling target tracking includes determining whether a tracking mode of a movable object is a manual tracking mode or an automatic tracking mode; when it is determined that the tracking mode is the manual tracking mode, determining a target for the movable object from one or more images based on a user input; when it is determined that the tracking mode is the automatic tracking mode, having the movable object determine the target automatically; and directing the movable object to track a target object using the target.

System and method for supporting smooth target following

A computer-implemented method for controlling a UAV includes identifying a set of target markers based on a plurality of images captured by an imaging device carried by the UAV, and controlling the UAV to fly based on the set of target markers. The set of target markers include at least two or more types of target markers and are in close proximity to be detected within a same field of view of the imaging device. Controlling the UAV to fly includes controlling the UAV to approach the set of target markers based at least in part on a spatial relationship between the UAV and a first type of target marker; and determining whether to control the UAV to land at or near the set of target markers based on information conveyed by a second type of target marker.

Methods and system for autonomous landing

Systems, methods, and computer-readable storage devices for obstacle detection may include an exemplary method of obstacle detection by a computing device. The method includes receiving a first dataset indicating a first surrounding with a first perspective; receiving a second dataset indicating a second surrounding with a second perspective; and generating a composite dataset from the first and second datasets. The method additionally includes identifying an obstacle using the composite dataset.

Systems and methods for coordinating device actions

A hybrid driving system and a hybrid electric vehicle. The hybrid driving system includes an engine, an input element (), an output element (), a box body (), a first motor (), a second motor (), a first planet row, a second planet row, a third planet row, a first clutch () and a first brake (). According to the hybrid driving system of the present disclosure, a basic three-planet-row planet gear configuration is provided through the planet row mechanical structure and the reasonable layout of multiple operating elements (the clutches and the brakes), which can realize at least two E-CVT working modes to obtain higher transmission efficiency.

Hybrid driving system and hybrid electric vehicle

The present disclosure provides a gimbal adjustment method. The method includes obtaining a reference image frame sequence and a reference shooting trajectory formed by a movement of a mobile platform when shooting the reference image frame sequence, the reference image frame sequence including two or more reference image frames, the mobile platform including a gimbal and an imaging assembly; estimating a shooting angle based on the reference shooting trajectory, and adjusting the gimbal based on an estimated shooting angle during an image re-shooting; obtaining a current image frame; and determining an amount of adjustment control of the gimbal based on the current image frame and the reference image frame sequence, and adjusting the gimbal based on the amount of adjustment control.

Gimbal adjustment method, gimbal adjustment device, mobile platform and storage medium

A method includes generating one or more calibration instructions for calibrating one or more sensors coupled to a movable object and providing at least some of the one or more calibration instructions to a user interface. The at least some of the one or more calibration instructions includes human-readable user instructions for moving the movable object along a predetermined pattern. The method further includes calibrating one or more sensor parameters for the one or more sensors based at least in part on sensor data collected while the movable object moves along the predetermined pattern.

Simple multi-sensor calibration

A control method for a mobile robot includes: obtaining indication information of a target object, wherein the indication information includes position information of the target object in a reference image output by a photographic apparatus of a mobile robot; determining the position information of the target object according to the indication information; and controlling, according to the position information of the target object, the mobile robot to move around the target object. With the provided control methods and apparatuses, devices, and storage media, the mobile robot may move around the target object without needing to move to a circling center to record a position of the circling center.

Mobile robot orbiting photography path control methods and apparatuses

A pose determination method for a subject includes identifying a plurality of candidate regions from depth data representing an environment based on a depth connectivity criterion, determining a first region including a first subset of the plurality of candidate regions based on an estimation regarding a first pose component of the subject, determining a second region including a second subset of the plurality of candidate regions that are disconnected from the first subset of the plurality of candidate regions based on relative locations of the first region and the second region, generating a collective region by associating the first region with the second region, identifying the first pose component and a second pose component of the subject from the collective region, determining a spatial relationship between the first pose component and the second pose component, and generating a controlling command based on the spatial relationship.

Depth information based pose determination for mobile platforms, and associated systems and methods

A computer-implemented method for controlling an unmanned aerial vehicle (UAV) includes identifying a set of target markers based on a plurality of images captured by an imaging device carried by the UAV. The set of target markers includes at least two or more types of target markers that are in close proximity to be detected within a same field of view of the imaging device. The method further includes determining a spatial relationship between the UAV and the set of target markers based at least in part on the plurality of images, and controlling the UAV to approach the set of target markers based at least in part on the spatial relationship while controlling the imaging device to track the set of target markers such that the set of target markers remains within the same field of view of the imaging device.

Growing community of inventors

Shenzhen, China

You Zhou