Model learning for robot control: a survey
D Nguyen-Tuong, J Peters - Cognitive processing, 2011 - Springer
Abstract Models are among the most essential tools in robotics, such as kinematics and
dynamics models of the robot's own body and controllable external objects. It is widely …
dynamics models of the robot's own body and controllable external objects. It is widely …
On-line regression algorithms for learning mechanical models of robots: a survey
With the emergence of more challenging contexts for robotics, the mechanical design of
robots is becoming more and more complex. Moreover, their missions often involve …
robots is becoming more and more complex. Moreover, their missions often involve …
R-iac: Robust intrinsically motivated exploration and active learning
A Baranes, PY Oudeyer - IEEE Transactions on Autonomous …, 2009 - ieeexplore.ieee.org
Intelligent adaptive curiosity (IAC) was initially introduced as a developmental mechanism
allowing a robot to self-organize developmental trajectories of increasing complexity without …
allowing a robot to self-organize developmental trajectories of increasing complexity without …
The hierarchical operational space formulation: Stability analysis for the regulation case
The Operational Space Formulation (OSF) from the 1980s is probably the most frequently
applied task-space controller in robotics. In multipriority control of redundant robots via the …
applied task-space controller in robotics. In multipriority control of redundant robots via the …
Task accuracy enhancement for a surgical macro-micro manipulator with probabilistic neural networks and uncertainty minimization
F Cursi, W Bai, EM Yeatman… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …
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 …
Model learning with backlash compensation for a tendon-driven surgical robot
F Cursi, W Bai, EM Yeatman… - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
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 …
Adaptive kinematic modelling for multiobjective control of a redundant surgical robotic tool
Accurate kinematic models are essential for effective control of surgical robots. For tendon
driven robots, which are common for minimally invasive surgery, the high nonlinearities in …
driven robots, which are common for minimally invasive surgery, the high nonlinearities in …
Robot learning
Abstract Machine learning offers to robotics a framework and set of tools for the design of
sophisticated and hard-to-engineer behaviors; conversely, the challenges of robotic …
sophisticated and hard-to-engineer behaviors; conversely, the challenges of robotic …
Subspace-oriented energy distribution for the time domain passivity approach
C Ott, J Artigas, C Preusche - 2011 IEEE/RSJ International …, 2011 - ieeexplore.ieee.org
The Time Domain Passivity Control Approach (TDPA) is a powerful tool to guarantee
passive interaction between a robot and its environment. Rather than establishing fixed …
passive interaction between a robot and its environment. Rather than establishing fixed …