Abstract: A method and a system for comprehensively evaluating reliability of a multi-chip parallel IGBT module are provided. The method includes: establishing a gate-emitter voltage reliability model of the multi-chip parallel IGBT module, performing a chip fatigue failure test, and selecting a gate-emitter voltage as a failure characteristic quantity; establishing a transconductance reliability model of the multi-chip parallel IGBT module, performing a bonding wire shedding failure test, and selecting a transmission characteristic curve of the module as a failure characteristic quantity; using a Pearson correlation coefficient to characterize a degree of health of the IGBT module, and respectively calculating degrees of health PPMCCC and PPMCCB in different degrees of chip fatigue and bonding wire shedding failure states; and comprehensively evaluating the reliability of the multi-chip parallel IGBT module according to PPMCCC and PPMCCB.

Abstract: A wheelchair structure includes a seat body, a rear wheel bracket, a push rod device, and two relatively arranged front wheel assemblies, where the front wheel assembly includes a support member and a first wheel body mounted at the bottom end of the support member, the seat body and the rear wheel bracket are rotatably connected between the support members of the two front wheel assemblies, the push rod device includes a push rod and a driving mechanism for driving the push rod to make a telescopic movement, a first end of the push rod is rotatably connected with the bottom of the seat body, a second end of the push rod is rotatably connected with the rear wheel bracket, the push rod makes the telescopic movement to drive the seat body to rotate between the support members of the two front wheel assemblies.

Abstract: A hand trajectory recognition method for a following robot based on hand velocity and trajectory distribution comprises: sampling and photographing an operator by a kinect camera to obtain hand projection plane data; smoothing the hand projection plane data by moving average, establishing velocity vectors, and processing the velocity vectors to obtain a hand movement descriptor; establishing a hand movement area, traversing hand three-dimensional positions of all frames in an order of sampling and photographing, assigning a mesh where the hand three-dimensional position of each frame is located, and calculating centroid positions of all assigned meshes; establishing centroid directing vectors, and processing the centroid directing vectors to obtain a hand trajectory shape descriptor; and processing cosine values of two angles to obtain a common similarity of the movement descriptor and the trajectory shape descriptor to standard descriptors, and using a standard gesture with a maximum common similarity as a r

Abstract: Systems and methods for detecting restricted traffic zones for autonomous driving are disclosed. In one aspect, method, includes receiving output from a perception system of an autonomous vehicle and detecting, based on the output from the perception system, one or more objects indicating a presence of a restricted traffic zone. The method may further include determining that the autonomous vehicle is entering the restricted traffic zone based on at least one of a prior map, an obstruction map, and the detected one or more objects.

Abstract: A lidar-based prior map for estimating static objects via deep-learning algorithm is disclosed. In one aspect, a server includes a network communication device configured to communicate with a plurality of autonomous vehicles over a network, a memory, and a processor. The processor is configured to receive LiDAR data from the autonomous vehicles, generate a LiDAR prior map comprising raw data based on the LiDAR data received from each of the autonomous vehicles, merge the raw data into a prior map, the prior map comprising an occupancy grid indicative of locations of static objects within an environment of the autonomous vehicles, and provide the prior map to the autonomous vehicles.

Abstract: Systems and methods for updating navigational maps based using at least one sensor are provided. In one aspect, a control system for an autonomous vehicle, includes a processor and a computer-readable memory configured to cause the processor to: receive output from at least one sensor located on the autonomous vehicle indicative of a driving environment of the autonomous vehicle, retrieve a navigational map used for driving the autonomous vehicle, and detect one or more inconsistencies between the output of the at least one sensor and the navigational map. The computer-readable memory is further configured to cause the processor to: in response to detecting the one or more inconsistencies, trigger mapping of the driving environment based on the output of the at least one sensor, update the navigational map based on the mapped driving environment, and drive the autonomous vehicle using the updated navigational map.

Abstract: Systems and methods for updating navigational maps based using at least one sensor are provided. In one aspect, a control system for an autonomous vehicle, includes a processor and a computer-readable memory configured to cause the processor to: receive output from at least one sensor located on the autonomous vehicle indicative of a driving environment of the autonomous vehicle, retrieve a navigational map used for driving the autonomous vehicle, and detect one or more inconsistencies between the output of the at least one sensor and the navigational map. The computer-readable memory is further configured to cause the processor to: in response to detecting the one or more inconsistencies, trigger mapping of the driving environment based on the output of the at least one sensor, update the navigational map based on the mapped driving environment, and drive the autonomous vehicle using the updated navigational map.

Abstract: Systems and methods for updating navigational maps based using at least one sensor are provided. In one aspect, a control system for an autonomous vehicle, includes a processor and a computer-readable memory configured to cause the processor to: receive output from at least one sensor located on the autonomous vehicle indicative of a driving environment of the autonomous vehicle, retrieve a navigational map used for driving the autonomous vehicle, and detect one or more inconsistencies between the output of the at least one sensor and the navigational map. The computer-readable memory is further configured to cause the processor to: in response to detecting the one or more inconsistencies, trigger mapping of the driving environment based on the output of the at least one sensor, update the navigational map based on the mapped driving environment, and drive the autonomous vehicle using the updated navigational map.

Abstract: A hand trajectory recognition method for a following robot based on hand velocity and trajectory distribution comprises: sampling and photographing an operator by a kinect camera to obtain hand projection plane data; smoothing the hand projection plane data by moving average, establishing velocity vectors, and processing the velocity vectors to obtain a hand movement descriptor; establishing a hand movement area, traversing hand three-dimensional positions of all frames in an order of sampling and photographing, assigning a mesh where the hand three-dimensional position of each frame is located, and calculating centroid positions of all assigned meshes; establishing centroid directing vectors, and processing the centroid directing vectors to obtain a hand trajectory shape descriptor; and processing cosine values of two angles to obtain a common similarity of the movement descriptor and the trajectory shape descriptor to standard descriptors, and using a standard gesture with a maximum common similarity as a r

Abstract: A method of aligning optical axes of cameras for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs comprise instructions, which when executed by a computing device, cause the computing device to perform by one or more autonomous vehicle driving modules execution of processing of images using the following steps comprising: disposing a planar pattern that is viewable to a set of cameras; recovering boundary corner points of the planar pattern from a pair of images; constructing a pair of parallel lines based on 2D positions of the recovered boundary corner points; and determining an intersection point of the pair of parallel lines to be a vanishing point in a pixel coordinate.

Abstract: A wheelchair structure includes a seat body, a rear wheel bracket, a push rod device, and two relatively arranged front wheel assemblies, where the front wheel assembly includes a support member and a first wheel body mounted at the bottom end of the support member, the seat body and the rear wheel bracket are rotatably connected between the support members of the two front wheel assemblies, the push rod device includes a push rod and a driving mechanism for driving the push rod to make a telescopic movement, a first end of the push rod is rotatably connected with the bottom of the seat body, a second end of the push rod is rotatably connected with the rear wheel bracket, the push rod makes the telescopic movement to drive the seat body to rotate between the support members of the two front wheel assemblies.

Abstract: A method of aligning optical axes of cameras for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs comprise instructions, which when executed by a computing device, cause the computing device to perform by one or more autonomous vehicle driving modules execution of processing of images using the following steps comprising: calibrating intrinsic parameters of a set of cameras; extracting corner points associated with a pattern; and computing a vanishing point based on information on the extracted corner points.

Abstract: A system for generating a ground truth dataset for motion planning is disclosed. The system includes sensors for data acquisition for motion planning of a vehicle, the sensors including a LiDAR; a calculating module configured to calculate LiDAR poses in response to data from the sensors and generate undistorted LiDAR scans; an extracting module configured to extract static points from a target undistorted LiDAR scan and generate a LiDAR static-scene point cloud; and a generating module configured to generate sparse image point correspondences for each pair of images, using the LiDAR static-scene point cloud.

Abstract: A method of generating a ground truth dataset for motion planning is disclosed. The method includes performing data alignment, collecting data in an environment, using sensors, calculating, among other sensors, light detecting and ranging (LiDAR)'s poses, stitching multiple LiDAR scans to form a local map, refining positions in the local map based on a matching algorithm, and projecting 3D points in the local map onto corresponding images.

Abstract: An embedded touch panel (100) having a high resistance film (70) comprises a sequentially stacked first substrate (10), thin-film transistor substrate (20), liquid crystal layer (30), color filter (40), touch sensing layer (50), second substrate (60), and the high resistance film (70). A plurality of mutually insulated sensing wires are disposed on a surface of the thin-film transistor substrate (20) facing toward the liquid crystal layer (30). The thin-film transistor substrate (20) and the touch sensing layer (50) work together to embed a functionality of a touch panel into liquid crystal pixels, reducing a thickness of the touch panel (100). The high resistance film (70) is disposed on a surface of the second substrate (60) facing away from the touch sensing layer (50), and is electrically connected to the thin-film transistor substrate (20).

Abstract: A touch control display device having a high resistance layer and a preparation method thereof, the touch control display device (100) having a high resistance layer comprising, stacked sequentially, a thin film transistor substrate (10), a touch control sensing layer (40), a liquid crystal layer (20), a color optical filter substrate (30) and a high resistance layer (50). The material of the high resistance layer (50) is a mixture of graphite oxide and tin oxide.

Abstract: A method of aligning optical axes of cameras for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs comprise instructions, which when executed by a computing device, cause the computing device to perform by one or more autonomous vehicle driving modules execution of processing of images using the following steps comprising: calibrating intrinsic parameters of a set of cameras; extracting corner points associated with a pattern; and computing a vanishing point based on information on the extracted corner points.

Abstract: A method of aligning optical axes of cameras for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs comprise instructions, which when executed by a computing device, cause the computing device to perform by one or more autonomous vehicle driving modules execution of processing of images using the following steps comprising: disposing a planar pattern that is viewable to a set of cameras; recovering boundary corner points of the planar pattern from a pair of images; constructing a pair of parallel lines based on 2D positions of the recovered boundary corner points; and determining an intersection point of the pair of parallel lines to be a vanishing point in a pixel coordinate.

Abstract: A system for generating a ground truth dataset for motion planning is disclosed. The system includes sensors for data acquisition for motion planning of a vehicle, the sensors including a LiDAR; a calculating module configured to calculate LiDAR poses in response to data from the sensors and generate undistorted LiDAR scans; an extracting module configured to extract static points from a target undistorted LiDAR scan and generate a LiDAR static-scene point cloud; and a generating module configured to generate sparse image point correspondences for each pair of images, using the LiDAR static-scene point cloud.

Abstract: A method of generating a ground truth dataset for motion planning is disclosed. The method includes performing data alignment, collecting data in an environment, using sensors, calculating, among other sensors, light detecting and ranging (LiDAR)'s poses, stitching multiple LiDAR scans to form a local map, refining positions in the local map based on a matching algorithm, and projecting 3D points in the local map onto corresponding images.