Optimization based Trajectory Planning of Mobile Cable-Driven Parallel Robots

A Mobile Cable-Driven Parallel Robot (MCDPR) is composed of a classical Cable-Driven Parallel Robot (CDPR) carried by multiple mobile bases. The additional mobilities due the motion of the mobile bases allow such systems to autonomously modify their geometric architecture, and thus make them suitable for multiple manipulation tasks in constrained environments. Moreover, these additional mobilities mean MCDPRs are kinematically redundant and may use this redundancy to optimize secondary task criteria. However, the high dimensional state space and closed chain constraints add complexity to the motion planning problem. To overcome this, we propose a method for trajectory planning for MCDPRs performing pick and place operations in cluttered environments by using direct transcription optimization. Two different scenarios have been considered and their results are validated using a dynamic simulation software (V-REP) and experimentally.

Authors

• Tahir Rasheed
• Philip Long
• Adolfo Suarez-Roos
• Stéphane Caro

Keywords

• Parallel robots
• Trajectory planning
• Redundancy
• Dynamics
• Computer architecture
• Software
• Planning
• Complexity theory
• Optimization
• Intelligent robots
• Parallel Robot
• Cable-driven Parallel Robots
• High-dimensional State Space
• Discretion
• Time Step
• Optimization Problem
• Transition State
• State Variables
• Cubic Spline
• Workspace
• Dimensional Vector
• Point-like
• Equality Constraints
• Path Planning
• Mobile Robot
• Trajectory Optimization
• Static Equilibrium
• Continuous Path
• State Transition Matrix
• Maximum Tension
• CPU Time In Seconds
• Continuous Trajectory
• Collision-free Path
• Actuator
• Rotational Motion
• Experimental Validation