Nothing Special   »   [go: up one dir, main page]

de Souza et al., 2021 - Google Patents

Reconfigurable grasp planning pipeline with grasp synthesis and selection applied to picking operations in aerospace factories

de Souza et al., 2021

View PDF
Document ID
16962876522851544943
Author
de Souza J
Costa C
Rocha L
Arrais R
Moreira A
Pires E
Boaventura-Cunha J
Publication year
Publication venue
Robotics and Computer-Integrated Manufacturing

External Links

Snippet

Several approaches with interesting results have been proposed over the years for robot grasp planning. However, the industry suffers from the lack of an intuitive and reliable system able to automatically estimate grasp poses while also allowing the integration of …
Continue reading at repositorio.inesctec.pt (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
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/40—Robotics, robotics mapping to robotics vision
    • G05B2219/40053—Pick 3-D object from pile of objects
    • 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
    • G05B2219/32—Operator till task planning
    • 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
    • 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
    • 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
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
    • 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
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50—Computer-aided design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer

Similar Documents

Publication Publication Date Title
de Souza et al. Reconfigurable grasp planning pipeline with grasp synthesis and selection applied to picking operations in aerospace factories
Bicchi On the closure properties of robotic grasping
Shimoga Robot grasp synthesis algorithms: A survey
Nguyen Constructing force-closure grasps
Li et al. Dexterous grasping under shape uncertainty
Nakamura et al. Task-priority based redundancy control of robot manipulators
Hart et al. Learning generalizable control programs
Huang et al. Learning a real time grasping strategy
Patel et al. Task based synthesis of serial manipulators
Honarpardaz et al. Fast finger design automation for industrial robots
Shi et al. Real-time grasping planning for robotic bin-picking and kitting applications
Hossain et al. Pick-place of dynamic objects by robot manipulator based on deep learning and easy user interface teaching systems
Vu et al. Machine learning-based framework for optimally solving the analytical inverse kinematics for redundant manipulators
Zhang et al. Trajectory planning based on non-convex global optimization for serial manipulators
Liu et al. Serocs: Safe and efficient robot collaborative systems for next generation intelligent industrial co-robots
Zhang et al. Industrial robot programming by demonstration
Manitsaris et al. Human movement representation on multivariate time series for recognition of professional gestures and forecasting their trajectories
Mohammed et al. Selection and Evaluation of Robotic Arm based Conveyor Belts (RACBs) Motions: NARMA (L2)-FO (ANFIS) PD-I based Jaya Optimization Algorithm.
Ren et al. Enabling Versatility and Dexterity of the Dual-Arm Manipulators: A General Framework Toward Universal Cooperative Manipulation
Sun et al. A Fuzzy Cluster-Based Framework for Robot–Environment Collision Reaction
Iklima et al. Self-collision avoidance of arm robot using generative adversarial network and particles swarm optimization (gan-pso)
Tao et al. A method for robotic grasping based on improved Gaussian mixture model
Zhang et al. A visual imitation learning algorithm for the selection of robots’ grasping points
Nambiar et al. Automation of unstructured production environment by applying reinforcement learning
Roa et al. Regrasp planning in the grasp space using independent regions