Abstract
To improve the positioning accuracy of collaborative robots, a novel modeling and calibration method for collaborative robots is proposed based on position information and modified local product of exponentials (LPoE). The kinematic error model is derived from the kinematic model through differential transformation. To solve the problem of the high redundancy and complexity of the error model that is difficult to identify, the errors of the kinematic parameters are all transferred to the initial position and posture matrix of the local coordinate system, which simplifies the error model and improves the speed and accuracy of the identification calculation. However, the simplified error model still requires posture data which are very difficult to acquire in practice. For this reason, the position error is separated from the kinematic model, and an error model based on position data is established. Then, a kinematic calibration method of the collaborative robot based on position data is proposed, which simplifies the measurement process and improves the efficiency of calibration. The effectiveness of the method is verified by simulations and experiments on a six degree-of-freedom collaborative robot.
Highlights
With the development of robots and the change of manufacturing mode, the working field of robots is expanding to realize natural interaction with humans, e.g., collaborative robots begin to be applied in unstructured environments to cooperate with humans
To further verify the calibration method based on position information and local product of exponentials (LPoE) model proposed in this paper, a calibration experiment was carried out on a six degree-offreedom collaborative robot, the repeated positioning accuracy of which is 0.03 mm
The kinematic model of the collaborative robot based on the LPoE model was established, and the corresponding error model and calibration method were derived
Summary
With the development of robots and the change of manufacturing mode, the working field of robots is expanding to realize natural interaction with humans, e.g., collaborative robots begin to be applied in unstructured environments to cooperate with humans. The PoE error model contains a finite integral term, which is not an explicit form and is inconvenient to use leading to the identifiability of its kinematic parameters cannot be determined [16]. He et al [17] modified the PoE model by deriving the differential solution formula of exponential mapping on joint twists and variables and established an error model based on PoE model with explicit expression, which is the main PoE method used in kinematic calibration at present. A kinematic calibration method of collaborative robot based on position data is proposed, which simplifies the measurement process and improves the efficiency of calibration
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