Abstract: A micro-robot magnetic drive device and a control method based on double closed loop three-dimensional path tracking are disclosed. The method includes: inputting a desired tracking path, obtaining current pose information of a magnetic micro-robot through a camera, and then calculating a position of a center of mass, an actual axial direction, coordinates of a desired position point with the shortest distance from the center of mass on a desired tracking path, and a tangent direction of this point; calculating a horizontal distance, a vertical distance, a direction angle error, and a pitch angle error of the two points according to the actual axial direction, the tangent direction, and disturbance compensation; and obtaining a required rotating magnetic field according to a designed position closed loop controller.

Abstract: A micro-robot magnetic drive device and a control method based on double closed loop three-dimensional path tracking are disclosed. The method includes: inputting a desired tracking path, obtaining current pose information of a magnetic micro-robot through a camera, and then calculating a position of a center of mass, an actual axial direction, coordinates of a desired position point with the shortest distance from the center of mass on a desired tracking path, and a tangent direction of this point; calculating a horizontal distance, a vertical distance, a direction angle error, and a pitch angle error of the two points according to the actual axial direction, the tangent direction, and disturbance compensation; and obtaining a required rotating magnetic field according to a designed position closed loop controller.

Abstract: The present invention relates to the field of pedestrian detection, and particularly relates to a multi-scale aware pedestrian detection method based on an improved full convolutional network. Firstly, a deformable convolution layer is introduced in a full convolutional network structure to expand a receptive field of a feature map. Secondly, a cascade-region proposal network is used to extract multi-scale pedestrian proposals, discriminant strategy is introduced, and a multi-scale discriminant layer is defined to distinguish pedestrian proposals category. Finally, a multi-scale aware network is constructed, a soft non-maximum suppression algorithm is used to fuse the output of classification score and regression offsets by each sensing network to generate final pedestrian detection regions.

Abstract: The present invention relates to the field of pedestrian detection, and particularly relates to a multi-scale aware pedestrian detection method based on an improved full convolutional network. Firstly, a deformable convolution layer is introduced in a full convolutional network structure to expand a receptive field of a feature map. Secondly, a cascade-region proposal network is used to extract multi-scale pedestrian proposals, discriminant strategy is introduced, and a multi-scale discriminant layer is defined to distinguish pedestrian proposals category. Finally, a multi-scale aware network is constructed, a soft non-maximum suppression algorithm is used to fuse the output of classification score and regression offsets by each sensing network to generate final pedestrian detection regions.