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WP1 - CoBotAGV Automated Guided Vehicle Integrated with Collaborative Robot


The collaborative robots are increasingly used in industry. However, they are often related to assembly stations. Currently, producers are required to quickly change production methods to be more effective. Using robots in various places allows to increase production efficiency. To move the robot to another assembly station AGV could be used. However, just moving the robot is not enough. To properly perform work, after moving it must be recalibrated to a new position on the new assembly station. Therefore, it is necessary to obtain methods of integration the robot with AGV and the required sensors, sensor fusion for the analysis of position of robot which enable development of methods enabling the recalibration of the mobile robot in a new assembly station. Additionally collaborative robot should be able to cooperate with staff at a new assembly station. It requires to obtain methods for quick teaching the robot the new moves necessary to work on a new assembly station.

In order to achieve overall objective of the WP1 four specific objectives have been defined:

  • Design and implementation of integration methods between AGV, collaborative robot and required sensors.
  • Implementation of precise docking of AGV to the assembly station.
  • Implementation of the recalibration methods for mobile collaborative robot.
  • Implementation of methods for cooperation between mobile collaborative robots and production staff.

Research tasks:

T1.1 Safe and effective integration between AGV and CR

This task focuses on integration between AGV and collaborative robot and the preparation of methods for precise docking of AGV to the assembly station:

  • implementation of a collaborative robot on AGV, including connection, communication and energy management methods,
  • integration of sensors for AGV which will allow for precise distance measurement to the assembly including use of various sensors (inclinometers, cameras (including ToF), optical encoders, lidars),
  • data fusion from sensors and navigation system including preparation of methods for precise docking of AGV to the assembly station.

T1.2 - Recalibration of the mobile robot reference system, positioning based on the fusion of position measurements

This task focuses on recalibration of the mobile collaborative robot reference system according to assembly station:

  • positioning of the robot for work implemented on the elements of vision, image recognition and the use of other sensors and their fusion and based on the camera image and data from other sensors, information about the assembly station offset in relation to the reference coordinate system for the robot,
  • movement of the robot arm, e.g. shifting of the arm to reference points on the assembly station will be used in order for precise force measurement on the selected axes. This will require the appointment of reference points for each robot axis in advance.
  • the analysis of the obtained data in order to more accurately determine the current position of the robot according to assembly station and correct the coordinate system for work,
  • recalibration with require high precision for e.g. automatic handling processes, in which the collaborative robot would have to pick up and put down details with high precision.

T1.3 - Cooperation between mobile collaborative robots and production staff, anticipating the operator's intentions

This task focuses on improving the functionality of collaborative robots in accordance with the operator's requirements:

  • Collaborative robots equipped with a handhold teaching function allow to record movements and then repeat them over shoulder with the interaction between human and robot
  • strategies for sharing control in different applications, collision handling and communication through selected interfaces,
  • Human-Robot Cooperative Learning methods to obtain new movements by robot,
  • data analysis of the learned movements by the robot and preparation methods and algorithms for their optimization by smoothing the movements, elimination of potential singularities and acceleration of work.

Research progress:


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