[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Jandaghi et al., 2023 - Google Patents

Motion dynamics modeling and fault detection of a soft trunk robot

Jandaghi et al., 2023

View PDF
Document ID
3746559286777569686
Author
Jandaghi E
Chen X
Yuan C
Publication year
Publication venue
2023 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)

External Links

Snippet

The field of soft robotics has been experiencing rapid growth, with researchers and engineers showing increasing interest due to the unique capabilities of these robots. Soft robots, characterized by their soft bodies and flexible structures, have demonstrated great …
Continue reading at par.nsf.gov (PDF) (other versions)

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
    • G05B13/04—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
    • G05B2219/40611—Camera to monitor endpoint, end effector position
    • 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
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • 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
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run

Similar Documents

Publication Publication Date Title
Hu et al. Three-dimensional deformable object manipulation using fast online gaussian process regression
Sutanto et al. Encoding physical constraints in differentiable newton-euler algorithm
Hu et al. Evolution strategies learning with variable impedance control for grasping under uncertainty
CN111319036B (en) Self-adaptive algorithm-based mobile mechanical arm position/force active disturbance rejection control method
Jandaghi et al. Motion dynamics modeling and fault detection of a soft trunk robot
Cho et al. Neural network based adaptive actuator fault detection algorithm for robot manipulators
CN105772917B (en) A kind of three joint spot welding robot's Trajectory Tracking Control methods
JP2014006566A (en) Built-in intelligence controller, control system, control program, recording medium, and control method
Mazare et al. Adaptive variable impedance control for a modular soft robot manipulator in configuration space
Hamedani et al. Adaptive impedance control of uncertain robot manipulators with saturation effect based on dynamic surface technique and self-recurrent wavelet neural networks
Chico et al. Hand gesture recognition and tracking control for a virtual UR5 robot manipulator
Khadivar et al. Adaptive fingers coordination for robust grasp and in-hand manipulation under disturbances and unknown dynamics
Wu et al. Space manipulator optimal impedance control using integral reinforcement learning
Sun et al. A Fuzzy Cluster-Based Framework for Robot–Environment Collision Reaction
Panda et al. Combined online and offline inverse dynamics learning for a robot manipulator
Mirrazavi Salehian et al. A dynamical system approach for catching softly a flying object: Theory and experiment
CN117733870A (en) Mechanical arm target capturing method, device and medium based on track prediction control
Tsuji et al. Online learning of virtual impedance parameters in non-contact impedance control using neural networks
CN116834014A (en) Intelligent cooperative control method and system for capturing non-cooperative targets by space dobby robot
Kormushev et al. Robot learning for persistent autonomy
Hu et al. Learning motor skills of reactive reaching and grasping of objects
Ivaldi et al. Approximate optimal control for reaching and trajectory planning in a humanoid robot
Feng et al. Reinforcement Learning-Based Impedance Learning for Robot Admittance Control in Industrial Assembly
Claassens An RRT-based path planner for use in trajectory imitation
Pavlichenko et al. Flexible-joint manipulator trajectory tracking with learned two-stage model employing one-step future prediction