A system and method are provided for facilitating hands free and precise movement, translation and repositioning of a movable mechanical apparatus, including an operating room lighting system, mounted to a mechanically-movable base component including, for example, an articulable or articulated robotic-type arm, according to user input pointing commands, including laser or other like pointing commands initiated by a user. The user provides hands free designation of a point of focus with a pointing device. A sensor associated with the movable mechanical apparatus automatically detects the designated point of focus and a processor determines and executes a scheme of movement for moving the movable mechanical apparatus from a current position to a position proximate to the designated point of focus. A collision avoidance scheme is also provided for safety and to alert the user as to the presence of any impediment in the determined scheme of movement.

A surveillance system may comprise one or more computing devices and one or more robotic surveillance devices. The one or more computing devices may be configured to obtain video data captured by one or more cameras. The one or more computing devices may analyze the video data to determine whether there is any trigger event. In response to determining that there is a trigger event, the one or more computing device may determine an optimal robotic surveillance device among the one or more robotic surveillance devices based on the trigger event and provide an instruction to the optimal robotic surveillance device. The optimal robotic surveillance device may be configured to perform a responding action in response to receiving the instruction.

An action learning method, including: acquiring human body moving image data; determining three-dimensional human body pose action data corresponding to the human body moving image data; matching the three-dimensional human body pose action data with atomic actions in a robot atomic action library to determine robot action sequence data corresponding to the human body moving image data; performing action continuity stitching on all robot sub-actions in the robot action sequence data sequentially; determining a continuous action learned by a robot from the robot action sequence data subjected to the action continuity stitching.

A method for controlling a robot includes: establishing a reference coordinate system; capturing a user's gaze direction of an indicated target; acquiring a sight line angle of the robot; acquiring a position of the robot; acquiring a linear distance between the robot and the user; calculating in real time a gaze plane in a user's gaze direction relative to the reference coordinate system based on the sight line angle of the robot, the position of the robot and the liner distance between the robot and the user; and smoothly scanning the gaze plane by the robot to search for the indicated target in the user's gaze direction.

A method for waking up a robot includes: acquiring sight range information when a voice command issuer issues a voice command; if the sight range information of the voice command issuer when issuing the voice command is acquired, determining, based on the sight range information, whether the voice command issuer gazes the robot when the voice command is issued; and determining that the robot is called if the voice command issuer gazes the robot.

A system enables teleoperation of a robot based on a pose of a subject. The system includes an image capturing device and an operator system controller that are remotely located from a robotic system controller and a robot. The image capturing device captures images of the subject. The operator system controller maps a processed version of the captured image to a three-dimensional skeleton model of the subject and generates body pose information of the subject in the captured image. The robotic system controller communicates with the operator system controller over a network. The robotic system controller generates a plurality of kinematic parameters for the robot and causes the robot to take a pose corresponding to the pose of the subject in the captured image.

A system enables teleoperation of a robot based on a pose of a subject. The system includes an image capturing device and an operator system controller that are remotely located from a robotic system controller and a robot. The image capturing device captures images of the subject. The operator system controller maps a processed version of the captured image to a three-dimensional skeleton model of the subject and generates body pose information of the subject in the captured image. The robotic system controller communicates with the operator system controller over a network. The robotic system controller generates a plurality of kinematic parameters for the robot and causes the robot to take a pose corresponding to the pose of the subject in the captured image.

A surveillance system may comprise one or more computing devices and one or more robotic surveillance devices. The one or more computing devices may be configured to obtain video data captured by one or more cameras. The one or more computing devices may analyze the video data to determine whether there is any trigger event. In response to determining that there is a trigger event, the one or more computing device may determine an optimal robotic surveillance device among the one or more robotic surveillance devices based on the trigger event and provide an instruction to the optimal robotic surveillance device. The optimal robotic surveillance device may be configured to perform a responding action in response to receiving the instruction.

A surveillance system may comprise one or more computing devices and one or more robotic surveillance devices. The one or more computing devices may be configured to obtain video data captured by one or more cameras. The one or more computing devices may analyze the video data to determine whether there is any trigger event. In response to determining that there is a trigger event, the one or more computing device may determine an optimal robotic surveillance device among the one or more robotic surveillance devices based on the trigger event and provide an instruction to the optimal robotic surveillance device. The optimal robotic surveillance device may be configured to perform a responding action in response to receiving the instruction.

A method for waking up a robot includes: acquiring sight range information when a voice command issuer issues a voice command; if the sight range information of the voice command issuer when issuing the voice command is acquired, determining, based on the sight range information, whether the voice command issuer gazes the robot when the voice command is issued; and determining that the robot is called if the voice command issuer gazes the robot.