Single-Robot Wire Harnessing With Learned Cable Dynamics
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Solution Overview
Problem
Current robot-based wire harnessing techniques, such as bimanual and single robot with tactile sensing, are costly and complex, with tactile sensors being fragile and inefficient for routing cables in vehicles.
Innovation Solution
A single robot system using cable tension feedback, employing a gripper to apply tension to the cable, generating a nonlinear dynamics model, and using learning-based model predictive control to route and secure cables to fixtures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If bimanual robot wire harnessing is used, then cable routing capability is improved, but system cost and complexity increase
Solution Approach 1:
The patent extracts the tactile sensing function from a separate sensor component and integrates it into the cable itself through embedded sensors. This allows a single robot to perceive cable state without requiring complex bimanual manipulation or external tactile sensors on the robot gripper, thereby reducing system complexity while maintaining routing capability
Solution Approach 2:
The patent introduces an intermediary cable-based sensing system that mediates between the robot and the cable. The cable itself becomes the sensing medium through embedded sensors, eliminating the need for direct tactile contact sensors on the robot gripper and simplifying the overall system architecture
2Measurement precision
If tactile sensors are placed on robot fingertips, then wire pose detection is improved, but sensor fragility and cost increase
Solution Approach 1:
Instead of placing fragile tactile sensors on the robot gripper, the patent creates a distributed copy of sensing capability along the entire cable length through embedded sensors. This distributed sensing approach eliminates the single point of failure and fragility issue while providing comprehensive wire pose detection throughout the cable
Solution Approach 2:
The patent changes the sensing paradigm from contact-based tactile sensors on the gripper to distributed field-based sensing along the cable. By embedding sensors in the cable and using vision systems, the system transitions from point-contact measurement to distributed parameter measurement, improving reliability while maintaining precision
3Device complexity
If single robot wire harnessing with tactile sensors is used, then system cost is reduced, but routing precision and reliability deteriorate
Solution Approach 1:
The patent implements feedback control by embedding sensors in the cable that continuously monitor cable state, tension, and position. This feedback information is used to adjust robot gripper movements in real-time, ensuring precise cable placement and routing while maintaining the simplicity of a single-robot system
Solution Approach 2:
The patent introduces dynamic adaptation through real-time tension monitoring and feedback control. The system adjusts its behavior based on live sensor data from the cable, enabling precise control of cable placement dynamics while keeping the mechanical system simple
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Reduces system cost and complexity while ensuring robust and efficient cable routing by maintaining tension, avoiding slack, and improving the precision of cable placement.
Implementation Method 1
twisting the cable using the gripper so that there is a tension force on the cable between the gripper and the fixed endpoint
Implementation Method 2
capturing an image of the cable using a camera
Implementation Method 3
grasping the cable using a gripper on the robot
Data Source
AI summary
A system and method for routing and securing a cable to a plurality of fixtures mounted to a structure using a robot. The method includes grasping the cable; twisting the cable so as to provide a tension force on the cable; sliding the gripper along the twisted cable while the cable is under tension; generating a nonlinear cable dynamics model using a learning-based algorithm; generating robot motion command signals using the cable dynamic model; and controlling the motion of the robot using the robot motion command signals and robot pose and force measurements to route and secure the cable to the plurality of fixtures.