Improved recurrent neural network-based manipulator control with remote center of motion constraints: experimental results
DOI10.1016/j.neunet.2020.07.033zbMath1493.70046OpenAlexW3048422314WikidataQ98721691 ScholiaQ98721691MaRDI QIDQ2057734
Publication date: 7 December 2021
Published in: Neural Networks (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/11311/1146530
recurrent neural networkredundant manipulatorremote center of motionrobot-assisted minimally invasive surgery
Neural networks for/in biological studies, artificial life and related topics (92B20) Automated systems (robots, etc.) in control theory (93C85) Robot dynamics and control of rigid bodies (70E60)
Related Items (1)
Cites Work
- Direct adaptive controller for uncertain MIMO dynamic systems with time-varying delay and dead-zone inputs
- Optimality conditions in convex optimization revisited
- Composite learning from adaptive backstepping neural network control
- Nonlinear recurrent neural networks for finite-time solution of general time-varying linear matrix equations
- Approximate neural optimal control with reinforcement learning for a torsional pendulum device
- An approximation algorithm for graph partitioning via deterministic annealing neural network
- Universal adaptive control for uncertain nonlinear systems via output feedback
- Exact Complexity Certification of Active-Set Methods for Quadratic Programming
- Global output feedback control for a class of nonlinear systems with unknown homogenous growth condition
- Robust Adaptive Control of Uncertain Nonlinear Systems in the Presence of Input Saturation and External Disturbance
This page was built for publication: Improved recurrent neural network-based manipulator control with remote center of motion constraints: experimental results