Abstract: The present disclosure provides an obstacle detection method as well as an apparatus and a robot using the same. The method includes: obtaining, through the sensor module, image(s); detecting an obstacle image of an obstacle from the image(s) according to characteristic(s) of the obstacle; extracting image feature(s) of the obstacle; obtaining, through the sensor module, a position of the obstacle; associating the image feature(s) of the obstacle with the position of the obstacle; calculating a motion state a the obstacle based on the position information of the obstacle at different moments; and estimating the position of the obstacle in a detection blind zone of the robot based on the motion state. In such a manner, it is capable of providing more accurate position information of the obstacle in the detection blind zone, which is beneficial to the robot to plan a safe and fast moving path.

Abstract: The present disclosure provides a robot visual image feature extraction method as well as an apparatus and a robot using the same. The method includes: collecting image data through visual sensor(s) of the robot, and collecting angular velocity data through inertial sensor(s) of the robot; calculating a relative pose between image frames in the image data based on the angular velocity data; extracting feature points of the first image frame in the image data; calculating a projection position of each feature point of the k-th image frame in the k+1-th image frame based on a relative pose between the k-th image frame and the k+1-th image frame; and searching for each feature point in the projection position in the k+1-th image frame, and performing a synchronous positioning and a mapping based on the searched feature point. In this manner, the feature points of dynamic objects are eliminated.

Abstract: The present disclosure provides a virtual rail based cruise method as well as an apparatus and a robot using the same. The method includes: obtaining a digital map including a virtual rail; performing a path planning based on the virtual rail, a current position of the robot, and a cruise end point to obtain a cruise path; and obtaining parameter(s) of the robot by calculating through a preset path tracking algorithm based on the cruise path and the current position of the robot, and controlling the robot based on the control parameter(s). In this manner, the problems of the prior art that needs to lay a rail or set an auxiliary device which causes high cost and inconvenience in usage as well as the rail needs to be re-laid or the auxiliary device needs to be reinstalled when the route is to be changed can be solved.

Abstract: The present disclosure provides a relocalization method including: obtaining submap boundary points; drawing a first submap based on the submap boundary points; extracting a second submap from the first submap; performing a template matching on a known map based on the second submap to obtain first matching results; obtaining second matching result each corresponding to each of the first matching results based on a positional relationship of the second submap in the first submap: matching boundary points in each of the second matching results with the submap boundary points to filter out third matching results from the second matching results; and selecting one of the third matching results as a relocalization result. The present disclosure further provides a robot. In the above-mentioned manner, it is capable of realizing a re localization with high accuracy, high preciseness, and low error rate while there are environmental changes.

Abstract: The present disclosure relates to positioning technology, and particularly to a positioning method a positioning device, and a robot. In which, the method includes: obtaining first location information of the target object at a current moment being predicted by an extended Kalman filter model at a last moment; obtaining second location information of the target object at the current moment being collected by a sensor; predicting third location information of the target object at the current moment through the extended Kalman filter model based on the first location information and the second location information; and determining an error value of the third location information under a preset constraint condition, and correcting the third location information according, to the error value to obtain final location information of the target object at the current moment.

Abstract: The present disclosure provides a relocalization method including: obtaining submap boundary points; drawing a first submap based on the submap boundary points; extracting a second submap from the first submap; performing a template matching on a known map based on the second submap to obtain first matching results; obtaining second matching result each corresponding to each of the first matching results based on a positional relationship of the second submap in the first submap: matching boundary points in each of the second matching results with the submap boundary points to filter out third matching results from the second matching results; and selecting one of the third matching results as a relocal i/at ion result. The present disclosure further provides a robot. In the above-mentioned manner, it is capable of realizing a re localization with high accuracy, high preciseness, and low error rate while there are environmental changes.

Abstract: The present disclosure provides a positioning method and an apparatus with the same. The method includes: obtaining, by die sensor set, current track node information of a current track node of a map on which the to-be-positioned device is located, where the current track node information includes a color of the current track node; and determining position information of the to-be-positioned device based on the track node information. In the above manner, the positioning of the to-be-positioned device in a specific map can be realized.

Abstract: The present disclosure provides an obstacle detection method as well as an apparatus and a robot using the same. The method includes: obtaining, through the sensor module, image(s); detecting an obstacle in of an obstacle from the image(s) according to characteristic(s) of the obstacle; extracting image feature(s) of the obstacle; obtaining, through the sensor module, a position of the obstacle; associating the image feature(s) of the obstacle with the position of the obstacle; calculating a motion state a the obstacle based on the position information of the obstacle at different moments; and estimating the position of the obstacle in a detection blind zone of the robot based on the motion state. In such a manner, it is capable of providing more accurate position information of the obstacle in the detection blind zone, which is beneficial to the robot to plan a safe and fast moving path.

Abstract: The present disclosure provides a robot visual image feature extraction method as well as an apparatus and a robot using the same. The method includes: collecting image data through visual sensor(s) of the robot, and collecting angular velocity data through inertial sensor(s) of the robot; calculating a relative pose between image frames in the image data based on the angular velocity data; extracting feature points of the first image frame in the image data; calculating a projection position of each feature point of the k-th image frame in the k+1-th image frame based on a relative pose between the k-th image frame and the k+1-th image frame; and searching for each feature point in the projection position in the k+1-th image frame, and performing a synchronous positioning and a mapping based on the searched feature point. In this manner, the feature points of dynamic objects are eliminated.

Abstract: The present disclosure provides a virtual rail based cruise method as well as an apparatus and a robot using the same. The method includes: obtaining a digital map including a virtual rail; performing a path planning based on the virtual rail, a current position of the robot, and a cruise end point to obtain a cruise path; and obtaining parameter(s) of the robot by calculating through a preset path tracking algorithm based on the cruise path and the current position of the robot, and controlling the robot based on the control parameter(s). In this manner, the problems of the prior art that needs to lay a rail or set an auxiliary device which causes high cost and inconvenience in usage as well as the rail needs to be re-laid or the auxiliary device needs to be reinstalled when the route is to be changed can be solved.

Abstract: The present disclosure provides a visual assisted distance-based SLAM method for a mobile robot, and a mobile robot using the same. The method includes: obtaining distance data frames and visual data frames, each of the visual data frames corresponds to one of the distance data frames, performing a loop closure detection based on a current visual data frame in the visual data frames to find a matched visual data frame; calculating a relative pose between the current visual data frame and the matched visual data frame; and performing a loop closure optimization on pose data of one or more frames between the current visual data frame and the matched visual data frame based on the relative pose. In the above-mentioned manner, the present disclosure can improve the accuracy of mapping and/or realizing fast relocalization.

Abstract: The present disclosure relates to positioning technology, and particularly to a positioning method a positioning device, and a robot. In which, the method includes: obtaining first location information of the target object at a current moment being predicted by an extended Kalman filter model at a last moment; obtaining second location information of the target object at the current moment being collected by a sensor; predicting third location information of the target object at the current moment through the extended Kalman filter model based on the first location information and the second location information; and determining an error value of the third location information under a preset constraint condition, and correcting the third location information according, to the error value to obtain final location information of the target object at the current moment.