Details

Autor(en) / Beteiligte

• Das, Swagatam
• Saha, Snehanshu
• Coello Coello, Carlos A
• Bansal, Jagdish Chand

Titel

Convolutional Neural Network for Parameter Identification of a Robot

Ist Teil von

• Advances in Data-Driven Computing and Intelligent Systems, 2023, Vol.653, p.523-534

Ort / Verlag

Singapore: Springer Singapore Pte. Limited

Erscheinungsjahr

2023

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Parametric identification is a crucial issue due to the possibility of emulating systems for motion control, collision detection, manufacturing, and other scientific areas. However, the conventional methodologies need an optimized trajectory to find all the parameters quickly. This paper shows an identification method based on a convolutional neural network to extract the dynamic parameters of a cartesian robot. First, the variables of position, velocity, acceleration, and torque with a set of parameters create an image with a conversion method. Second, the backpropagation algorithm trains the convolutional neural network to return the robot’s parameters. Finally, a time-spectral evaluation distance gives the affinity of the results. The simulations show that the identification achieved 0.9916, and the experimental robot met 0.9196.