3results about How to "Improve trajectory tracking performance" patented technology

The application relates to the technical field of cross-domain multi-modal robots, in particular to a land-air robot with high ground self-adaptability and a control method thereof. The land-air robot comprises an air movement unit, a ground movement unit and an automatic driving module. The air movement unit is used for providing flight power for the land-air robot, so that the land-air robot has a flight mode. The ground movement unit is arranged at the bottom of the air movement unit, so that the land-air robot has a ground movement mode. The ground movement unit comprises a movement module and a five-link wheel-foot mechanism symmetrically arranged on the left and right sides of the land-air robot. The movement module is used for adjusting the posture of the five-link wheel-foot mechanism, so that the land-air robot realizes dynamic balance and posture righting in the ground movement mode. The automatic driving module is electrically connected with the air movement unit and the ground movement unit. The land-air robot in the application can move on land and in the air, and has good trajectory tracking performance in the land-air dual mode.

This invention provides a deep learning-based method for multi-target pedestrian tracking, relating to the field of computer vision technology. The method includes: S1 acquiring video data, extracting frames from the video data to convert them into image frames, and preprocessing the image frames; S2 using an improved YOLOv5-s model to detect pedestrian targets in the image frames, obtaining the pedestrian targets; S3 using an improved Strong SORT model to track the pedestrian targets in each frame, assigning an ID to each tracked pedestrian, and generating pedestrian tracking results. This invention can accurately locate each pedestrian in a video and track their trajectory.

The application provides a path planning cooperative control method for ship-borne heterogeneous strong coupling unmanned equipment, relates to the technical field of intelligent control and path planning, and comprises the following steps: considering the longitudinal, transverse and yaw motion of an unmanned tractor and an unmanned carrier aircraft on the deck plane of an aircraft carrier, a three-degree-of-freedom coupling motion mathematical model of the heterogeneous unmanned equipment is established; a virtual force field is constructed according to an improved artificial potential field method, a field strength adjusting operator and a heading disturbance injection term are introduced, and discrete path points are generated; the discrete path points are converted into continuous expected trajectories by using a Gaussian smoothing function; precise trajectory tracking of the unmanned equipment is realized through an adaptive neural network double-layer control architecture, the upper layer controls the unmanned carrier aircraft, the lower layer controls the unmanned tractor, and cooperative control is realized by using the coupling relationship. The application introduces a first-order filter (dynamic surface control technology), effectively suppresses the differential explosion phenomenon, reduces the algorithm complexity, and improves the engineering applicability of the controller.