An automated vehicle comprising: a control unit configured to control movement of the automated vehicle to a location adjacent an estimated location of a drill hole; a scanning portion including one or more scanning devices configured to scan an area of terrain in the vicinity of the estimated location of the drill hole in order to determine an actual location of the drill hole, and to generate a point cloud representing at least a portion of the interior of the drill hole; at least one arm associated with the scanning portion, the at least one arm configured to move the scanning portion between a home position and one or more scanning positions; and an end effector associated with the at least one arm, the end effector being configured to perform one or more operations;
wherein, upon generating the point cloud, the at least one arm is configured, based on the point cloud, to position the end effector in substantial alignment with the drill hole so that the end effector can perform the one or more operations.

Robotic arm processing method and system based on 3D image are provided. The processing method includes: providing robotic arm 3D model data and processing environment 3D model data; obtaining workpiece 3D model data, and generating a processing path consisting of contact points according to the workpiece 3D model data, wherein a free end of a robotic arm moves along the processing path to complete a processing procedure; generating a posture candidate group according to a relationship according to each one of the contact points corresponding to the free end of the robotic arm; selecting an actual moving posture from the posture candidate group; moving the free end of the robotic arm to each corresponding one of the contact points according to the selected actual moving posture; and moving the free end of the robotic arm along the processing path according to the actual moving postures to perform the processing procedure.

An image processing method can suppress detection accuracy of a detection target object from being lowered even if the detection target object has a different surface condition because of the influence of various kinds of noise. The image processing method includes the following operations of generating a captured model edge image by executing edge extraction processing on a captured model image acquired by capturing a detection target object, executing pattern matching of the captured model edge image and a model edge image, calculating similarity at respective edge points in the model edge image in the pattern matching of the captured model edge image and the model edge image, selecting an edge point to be eliminated based on the similarity from among the respective edge points in the model edge image, and generating an edge image acquired by eliminating the selected edge point as a final model edge image.

A control device, a position control system, a position control method, and a recording medium are provided. The controller includes a feedback control unit and a position determination unit. The position determination unit acquires an encoder values from a driver at a cycle. The position determination unit acquires a measurement position obtained by measuring a positional relationship between a control object position and a target position by image processing, at a time interval that is longer than the cycle. The position determination unit determines an estimation interpolation position corresponding to the control object position by using the encoder value and the measurement position. The feedback control unit outputs control data for aligning the control object position at the target position by using the estimation interpolation position determined by the position determination unit to the driver.

Example embodiments may relate to methods and systems for selecting a grasp point on an object. In particular, a robotic manipulator may identify characteristics of a physical object within a physical environment. Based on the identified characteristics, the robotic manipulator may determine potential grasp points on the physical object corresponding to points at which a gripper attached to the robotic manipulator is operable to grip the physical object. Subsequently, the robotic manipulator may determine a motion path for the gripper to follow in order to move the physical object to a drop-off location for the physical object and then select a grasp point, from the potential grasp points, based on the determined motion path. After selecting the grasp point, the robotic manipulator may grip the physical object at the selected grasp point with the gripper and move the physical object through the determined motion path to the drop-off location.

An image acquisition unit acquires an image including an object, and a controller starts a visual servo using the acquired image, on the basis of at least one of an error in calibration, an error in installation of a robot, an error resulting from the rigidity of the robot, an error of a position where the robot has gripped the object, an error regarding imaging, and an error regarding a work environment. Additionally, the controller starts the visual servo when the distance between one point of a working unit of the robot and the object is equal to or greater than 2 mm.

A robot, wherein the robot operates on the basis of a picked-up image of at least a part of a work space of the robot picked up by an image pickup section, and a transparent member is disposed between the robot and the work space of the robot.

Systems and methods for operating a robotic surgical system are provided. The system includes a surgical tool, a manipulator comprising a base supporting links for controlling the tool, a navigation system comprising a tracker coupled to the tool and a localizer to monitor a state of the tracker. A controller acquires raw kinematic measurement data about a state of the tool relative to the base from the manipulator, known relationship data about the state of the tracker relative to the tool, and raw navigation data about the state of the tracker relative to the localizer from the navigation system. The controller combines this data to determine a raw relationship between the base and the localizer. The raw relationship is filtered for controlling the manipulator. The raw relationship or a less filtered version of the raw relationship is utilized to determine whether an error has occurred in the system.

A robot system and method are provided that move an articulable arm relative to a target object. Perception information corresponding to a position of the arm relative to the target object is acquired. Movement of the arm is controlled based on the perception information. After movement of the arm, predicted position information representative of a predicted positioning of the arm is provided using the perception information and control signal information. The arm is subsequently controlled using the predicted position information.

Example embodiments may relate to methods and systems for selecting a grasp point on an object. In particular, a robotic manipulator may identify characteristics of a physical object within a physical environment. Based on the identified characteristics, the robotic manipulator may determine potential grasp points on the physical object corresponding to points at which a gripper attached to the robotic manipulator is operable to grip the physical object. Subsequently, the robotic manipulator may determine a motion path for the gripper to follow in order to move the physical object to a drop-off location for the physical object and then select a grasp point, from the potential grasp points, based on the determined motion path. After selecting the grasp point, the robotic manipulator may grip the physical object at the selected grasp point with the gripper and move the physical object through the determined motion path to the drop-off location.