A Graph-Based Self-Calibration Technique for Cable-Driven Robots with Sagging Cable

The efficient operation of large-scale Cable-Driven Parallel Robots (CDPRs) relies on precise calibration of kinematic parameters and the simplicity of the calibration process. This paper presents a graph-based self-calibration framework that explicitly addresses cable sag effects and facilitates the calibration procedure for large-scale CDPRs by only relying on internal sensors. A unified factor graph is proposed, incorporating a catenary cable model to capture cable sagging. The factor graph iteratively refines kinematic parameters, including anchor point locations and initial cable length, by considering jointly onboard sensor data and the robot’s kineto-static model. The applicability and accuracy of the proposed technique are demonstrated through Finite Element (FE) simulations, on both large and small-scale CDPRs subjected to significant initialization perturbations.

Authors

• M. R. Dindarloo
• A. S. Mirjalili
• S. A. Khalilpour
• Rooholla Khorrambakht
• Stephan Weiss 0002
• Hamid D. Taghirad

Keywords

• Meters
• Accuracy
• Perturbation methods
• Kinematics
• Robot sensing systems
• End effectors
• Software
• Calibration
• Sensors
• Finite element analysis
• Cable-driven Robots
• Finite Element
• Calibration Procedure
• Calibration Process
• Kinematic Parameters
• Factor Graph
• Internal Sensors
• Unit Vector
• Horizontal Axis
• Energy Function
• Equation Of State
• Nonlinear Programming
• Graphical Model
• Nonlinear Least Squares
• Jacobian Matrix
• Force Sensor
• Calibration Results
• Local Frame
• Robot Model
• Laser Ranging
• Small Robot
• End-effector Pose
• Global Frame
• Linear Quadratic Gaussian
• Calibration Problem
• Sensory Measurements
• Height Of Point
• Subject Of Future Research
• Variable Nodes
• Cable-driven parallel robots
• Kinematic calibration
• Cable sag modeling
• Self-calibration