# US 2020/0401151 A1 · Device motion control > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2020/0401151 A1 - Document ID: US20200401151A1 - Status: Published application - Kind: A1 - Application number: 16/959,126 - Filed: 2018-11-12 - Published: 2020-12-24 - Earliest claimed: 2017-12-29 - Assignees: Beijing Sankuai Online Technology Co., Ltd - Applicants: Beijing Sankuai Online Technology Co., Ltd - Inventors: Yuda LIU - Web page: https://patentgrep.com/patent/US20200401151A1 ## CPC - G05D 1/0221: {involving a learning process} - G05D 1/0246: {using a video camera in combination with image processing means} - G05D 1/0202: {specially adapted to aircraft} - G05D 1/0242: {using non-visible light signals, e.g. IR or UV signals} - G05D 1/0248: {in combination with a laser (lasers per se H01S)} - G05D 1/0253: {extracting relative motion information from a plurality of images taken successively, e.g. visual odometry, optical flow (determining position or orientation from images G06T7/70)} - G06N 3/0464: Convolutional networks [CNN, ConvNet] - G06N 3/09: Supervised learning - G06N 3/045: Combinations of networks - G06N 3/08: Learning methods - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## Abstract Disclosed are a method and an apparatus for controlling device motion and an electronic device. The method includes: detecting position information of an object within a target range around a target device relative to the target device, acquiring image information collected by the target device, determining initial data based on the position information, the initial data including a plurality of sets of available values of a motion parameter, and selecting, from the plurality of sets of available values based on the image information, a target value of a current motion parameter for controlling motion of the target device. Therefore, the target device can be adjusted in real time according to a surrounding environment. ## Claims ### Claim 1 A method for controlling device motion, comprising: detecting position information of an object within a target range around a target device relative to the target device; acquiring image information collected by the target device; determining initial data based on the position information, the initial data comprising a plurality of sets of available values of a motion parameter; and selecting, from the plurality of sets of available values based on the image information, a target value of a motion parameter for currently controlling motion of the target device. ### Claim 2 (depends on 1) The method according to claim 1, wherein the initial data further comprises weights for each of the plurality of sets of available values; and the selecting, from the plurality of sets of available values based on the image information, a target value of the motion parameter for currently controlling motion of the target device comprises: modifying the weights for each of the plurality of sets of available values based on the image information; and selecting the target value from the plurality of sets of available values according to the modified weights for each of the plurality of sets of available values. ### Claim 3 (depends on 2) The method according to claim 2, wherein the modifying the weights for each of the plurality of sets of available values based on the image information comprises: determining modification data corresponding to each of the plurality of sets of available values based on the image information; and modifying the weights for each of the plurality of sets of available values according to the modification data. ### Claim 4 (depends on 3) The method according to claim 3, wherein the determined modification data corresponding to each of the plurality of sets of available values based on the image information comprises: inputting the image information into a pre-trained target convolutional neural network; acquiring a target angle output by the target convolutional neural network; and determining the modification data corresponding to each of the plurality of sets of available values based on the target angle. ### Claim 5 (depends on 4) The method according to claim 4, wherein the determining the modification data corresponding to each of the plurality of sets of available values based on the target angle comprises: generating a normal distribution function with the target angle as an expected value; and determining the modification data corresponding to each of the plurality of sets of available values according to the normal distribution function. ### Claim 6 (depends on 5) The method according to claim 5, wherein the motion parameter comprises a linear velocity and an angular velocity; and the determining the modification data corresponding to each of the plurality of sets of available values according to the normal distribution function comprises: determining a product of a preset duration and an available angular velocity in each of the plurality of sets of available values as a plurality of values of a random variable x of the normal distribution function; and acquiring a probability density value obtained by substituting each of the values into the normal distribution function as the modification data corresponding to each of the plurality of sets of available values. ### Claim at position 7 7-9. (canceled) ### Claim 10 An electronic device, comprising a storage medium, a processor, and a computer program stored in the storage medium and runnable on the processor, wherein when the processor executes the program, the processor is caused to: detect position information of an object within a target range around a target device relative to the target device; acquire image information collected by the target device; determine initial data based on the position information, the initial data comprising a plurality of sets of available values of a motion parameter; and select, from the plurality of sets of available values based on the image information, a target value of a motion parameter for currently controlling motion of the target device. ### Claim 11 (depends on 7) The device according to claim 7, wherein the initial data further comprises weights for each of the plurality of sets of available values; when selecting, from the plurality of sets of available values based on the image information, a target value of the motion parameter for currently controlling motion of the target device, the processor is caused to: modify the weights for each of the plurality of sets of available values based on the image information; and select the target value from the plurality of sets of available values according to the modified weights for each of the plurality of sets of available values. ### Claim 12 (depends on 8) The device according to claim 8, wherein when modifying the weights for each of the plurality of sets of available values based on the image information, the processor is caused to: determine modification data corresponding to each of the plurality of sets of available values based on the image information; and modify the weights for each of the plurality of sets of available values according to the modification data. ### Claim 13 (depends on 9) The device according to claim 9, wherein when determining modification data corresponding to each of the plurality of sets of available values based on the image information, the processor is caused to: input the image information into a pre-trained target convolutional neural network; acquire a target angle output by the target convolutional neural network; and determine the modification data corresponding to each of the plurality of sets of available values based on the target angle. ### Claim 14 (depends on 10) The device according to claim 10, wherein when determining the modification data corresponding to each of the plurality of sets of available values based on the target angle, the processor is caused to: generate a normal distribution function with the target angle as an expected value; and determine the modification data corresponding to each of the plurality of sets of available values according to the normal distribution function. ### Claim 15 (depends on 11) The device according to claim 11, wherein the motion parameter comprises a linear velocity and an angular velocity; when determining the modification data corresponding to each of the plurality of sets of available values according to the normal distribution function, the processor is caused to: determine a product of a preset duration and an available angular velocity in each of the plurality of sets of available values as a plurality of values of a random variable x of the normal distribution function; and acquire a probability density value obtained by substituting each of the values into the normal distribution function as the modification data corresponding to each of the plurality of sets of available values. ### Claim 16 A computer-readable storage medium, wherein the storage medium stores a computer program, and by executing the computer program, a processor is caused to: detect position information of an object within a target range around a target device relative to the target device; acquire image information collected by the target device; determine initial data based on the position information, the initial data comprising a plurality of sets of available values of a motion parameter; and select, from the plurality of sets of available values based on the image information, a target value of a motion parameter for currently controlling motion of the target device. ### Claim 17 (depends on 13) The storage medium according to claim 13, wherein the initial data further comprises weights for each of the plurality of sets of available values; when selecting, from the plurality of sets of available values based on the image information, a target value of the motion parameter for currently controlling motion of the target device, the processor is caused by the computer program to: modify the weights for each of the plurality of sets of available values based on the image information; and select the target value from the plurality of sets of available values according to the modified weights for each of the plurality of sets of available values. ### Claim 18 (depends on 14) The storage medium according to claim 14, wherein when modifying the weights for each of the plurality of sets of available values based on the image information, the processor is caused by the computer program to: determine modification data corresponding to each of the plurality of sets of available values based on the image information; and modify the weights for each of the plurality of sets of available values according to the modification data. ### Claim 19 (depends on 15) The storage medium according to claim 15, wherein when determining modification data corresponding to each of the plurality of sets of available values based on the image information, the processor is caused by the computer program to: input the image information into a pre-trained target convolutional neural network; acquire a target angle output by the target convolutional neural network; and determine the modification data corresponding to each of the plurality of sets of available values based on the target angle. ### Claim 20 (depends on 16) The storage medium according to claim 16, wherein when determining the modification data corresponding to each of the plurality of sets of available values based on the target angle, the processor is caused by the computer program to: generate a normal distribution function with the target angle as an expected value; and determine the modification data corresponding to each of the plurality of sets of available values according to the normal distribution function. ### Claim 21 (depends on 17) The storage medium according to claim 17, wherein the motion parameter comprises a linear velocity and an angular velocity; when determining the modification data corresponding to each of the plurality of sets of available values according to the normal distribution function, the processor is caused by the computer program to: determine a product of a preset duration and an available angular velocity in each of the plurality of sets of available values as a plurality of values of a random variable x of the normal distribution function; and acquire a probability density value obtained by substituting each of the values into the normal distribution function as the modification data corresponding to each of the plurality of sets of available values.