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Physics informed machine learning model for inverse dynamics in robotic manipulators
In the field of robotic modelling, the challenge of parameter estimation using limited joint
monitoring data presents a substantial hurdle for both traditional physics-based methods …
monitoring data presents a substantial hurdle for both traditional physics-based methods …
Model learning with backlash compensation for a tendon-driven surgical robot
Robots for minimally invasive surgery are becoming more and more complex, due to
miniaturization and flexibility requirements. The vast majority of surgical robots are tendon …
miniaturization and flexibility requirements. The vast majority of surgical robots are tendon …
Augmented neural network for full robot kinematic modelling in SE (3)
Due to the increasing complexity of robotic structures, modelling robots is becoming more
and more challenging, and analytical models are very difficult to build. Machine learning …
and more challenging, and analytical models are very difficult to build. Machine learning …
Task accuracy enhancement for a surgical macro-micro manipulator with probabilistic neural networks and uncertainty minimization
Accurate robot kinematic modelling is a major component for autonomous robot control to
guarantee safety and precision during task execution. In surgical robotics complex robotic …
guarantee safety and precision during task execution. In surgical robotics complex robotic …
Analysis of Efficient and Fast Prediction Method for the Kinematics Solution of the Steel Bar Grinding Robot
W Shi, J Zhang, L Li, Z Li, Y Zhang, X **ong, T Wang… - Applied Sciences, 2023 - mdpi.com
Aiming at the robotization of the grinding process in the steel bar finishing process, the steel
bar grinding robot can achieve the goal of fast, efficient, and accurate online grinding …
bar grinding robot can achieve the goal of fast, efficient, and accurate online grinding …