Zhang et al., 2023 - Google Patents
Adaptive safety-critical control with uncertainty estimation for human–robot collaborationZhang et al., 2023
View PDF- Document ID
- 6770676727276710329
- Author
- Zhang D
- Van M
- Mcllvanna S
- Sun Y
- McLoone S
- Publication year
- Publication venue
- IEEE Transactions on Automation Science and Engineering
External Links
Snippet
In advanced manufacturing, strict safety guarantees are required to allow humans and robots to work together in a shared workspace. One of the challenges in this application field is the variety and unpredictability of human behavior, leading to potential dangers for human …
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
- G05B13/027—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks only
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/39—Robotics, robotics to robotics hand
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/40—Robotics, robotics mapping to robotics vision
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Kong et al. | Adaptive fuzzy control for coordinated multiple robots with constraint using impedance learning | |
| Yang et al. | Neural networks enhanced adaptive admittance control of optimized robot–environment interaction | |
| Kim et al. | Obstacle avoidance method for wheeled mobile robots using interval type-2 fuzzy neural network | |
| Kim et al. | High-level feedback control with neural networks | |
| Zhu et al. | Real-time dynamic obstacle avoidance for robot manipulators based on cascaded nonlinear MPC with artificial potential field | |
| Zhang et al. | Adaptive safety-critical control with uncertainty estimation for human–robot collaboration | |
| Krug et al. | Model predictive motion control based on generalized dynamical movement primitives | |
| Park et al. | Adaptive formation control of electrically driven nonholonomic mobile robots with limited information | |
| Ebrahimi et al. | Intelligent Robust Fuzzy-Parallel Optimization Control of a Continuum Robot Manipulator | |
| Korayem et al. | Optimal point-to-point motion planning of non-holonomic mobile robots in the presence of multiple obstacles | |
| Rizzi et al. | Robust sampling-based control of mobile manipulators for interaction with articulated objects | |
| Batti et al. | Autonomous smart robot for path predicting and finding in maze based on fuzzy and neuro‐fuzzy approaches | |
| Piltan et al. | Design Artificial Intelligent Parallel Feedback Linearization of PID Control with Application to Continuum Robot | |
| Michaux et al. | Can't Touch This: Real-Time, Safe Motion Planning and Control for Manipulators Under Uncertainty | |
| Jalali et al. | Design Parallel Linear PD Compensation by Fuzzy Sliding Compensator for Continuum Robot | |
| Ngo et al. | Robust adaptive self-organizing wavelet fuzzy CMAC tracking control for de-icing robot manipulator | |
| Mamedov et al. | Safe Imitation Learning of Nonlinear Model Predictive Control for Flexible Robots | |
| Zhou et al. | Collision-free compliance control for redundant manipulators: an optimization case | |
| Wang et al. | Adaptive dynamic programming-based finite-time optimal backstepping force/position control of reconfigurable robot manipulators via Pareto optimal | |
| Piltan et al. | Stable fuzzy PD control with parallel sliding mode compensation with application to rigid manipulator | |
| Cheong et al. | Adaptive fuzzy dynamic surface sliding mode position control for a robot manipulator with friction and deadzone | |
| Wei et al. | Collision Avoidance for Convex Primitives via Differentiable Optimization-Based High-Order Control Barrier Functions | |
| Zheng et al. | Time‐Varying Impedance Control of Port Hamiltonian System with a New Energy‐Storing Tank | |
| CN118466186A (en) | A collision-free collaborative control method for human-machine collaboration in advanced manufacturing | |
| Izquierdo et al. | Optimal Trajectory Planning for Pneumatic Cylindrical Manipulator Considering Dynamical and Stick Slip Constraints |