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Multirobot Manipulation

Multirobot Manipulation. Ramon Costa Castelló Institut d’Organització i Control de Sistemes Industrials (IOC) Universitat Politècnica de Catalunya (UPC). Introduction. Motivations. Multirobot Manipulation Advantages Load Capacity Increase Dexterity Improvement Flexible Objects.

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Multirobot Manipulation

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  1. Multirobot Manipulation Ramon Costa Castelló Institut d’Organització i Control de Sistemes Industrials (IOC) Universitat Politècnica de Catalunya (UPC)

  2. Introduction

  3. Motivations • Multirobot Manipulation Advantages • Load Capacity Increase • Dexterity Improvement • Flexible Objects

  4. Robot System Programming Workspace Path Planning path Trajectory Planning trajectory Low level control loop Adaptation Position velocity Dynamics and kinematics force Environment

  5. Position controlled Manipulators Force Sensors Rigid Objects Rigid Grasping H Hd R(z) Experimental Constraints

  6. RX-90 RX-90 JR3 JR3 ISA BUS Serial Line Controller PC-QNX Experimental Setup • Experimental Setup: Work cell composed by two RX-90 Stäubli manipulators (in ALTER mode), each manipulator having a JR3 force sensor on its wrist

  7. Internal Forces • Coordinated Manipulation may apply undesired forces over manipulated object • Internal forces sources • inaccurate modelling • lack of synchronization • Goal • Keep internal forces under control • Desired load distribution

  8. Environment Environment Robot i Robot j Robot i Robot j control control control Classical Approaches • Hybrid Control • Force-position Decomposition • Centralized approach • Structured Environments • Explicit Control • Impedance behaviour • Relation Between force and position • Decentralized approach • Unstructured environments • Implicit Control

  9. Workspace Reduction • Kinematics Constraints Reduce Multirobot Workspace (only on cooperative manipulation). • Workspace defined by implicit equations.

  10. Detailed Topics • Workspace Analysis Results • Hybrid Control Results • Impedance Control Results

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