The present invention relates to a system for detecting the collision of a robot manipulator using an artificial neural network. The system may comprise: joint driving units provided in a plurality of joints of the robot manipulator to drive the plurality of joints, respectively; encoder units provided on sides of the joint driving units to measure the angles of the plurality of joints; and a neural network calculation unit for training the neural network with a large amount of data and inferring, via a preprocessing calculation, to detect that the plurality of joints collide with the outside.

A flexible manipulator apparatus includes an elongate flexible manipulator having a sensor, a user output device configured to provide sensory outputs to the user, and processing circuitry. The flexible manipulator may be movable to form a curve in the flexible manipulator. The processing circuitry may be configured to receive captured sensor data from the sensor during movement of the flexible manipulator, and determine a collision likelihood score based on application of the captured sensor data to a collision detection model used for position estimation. The collision detection model may be based on an empirical data training for the flexible manipulator that includes training sensor data from the sensor and training image data of positions of the flexible manipulator. The processing circuitry may be configured to control the user output device based on the collision likelihood score to provide a collision alert sensory output to the user.

A flexible manipulator apparatus includes an elongate flexible manipulator having a sensor, a user output device configured to provide sensory outputs to the user, and processing circuitry. The flexible manipulator may be movable to form a curve in the flexible manipulator. The processing circuitry may be configured to receive captured sensor data from the sensor during movement of the flexible manipulator, and determine a collision likelihood score based on application of the captured sensor data to a collision detection model used for position estimation. The collision detection model may be based on an empirical data training for the flexible manipulator that includes training sensor data from the sensor and training image data of positions of the flexible manipulator. The processing circuitry may be configured to control the user output device based on the collision likelihood score to provide a collision alert sensory output to the user.