Core Concepts
This paper presents an adaptive preload control (APC) method that allows cable-driven parallel robots to dynamically adjust their platform stiffness based on task requirements, enabling efficient handling operations.
Abstract
The paper presents a method for dynamically adjusting the cable preloads of cable-driven parallel robots (CDPRs) to increase or decrease the platform stiffness as needed for handling tasks.
Key highlights:
- The method exploits the actuation redundancy of CDPRs by computing preload parameters using an extended nullspace formulation of the kinematics.
- This allows the operator to specify a desired preload within the operation space, facilitating efficient handling operations.
- The algorithms are implemented in a real-time environment, enabling the use of optimization in hybrid position-force control.
- A simulation study is performed to validate the effectiveness of the approach, comparing it to existing methods.
- Experimental validation is conducted on the COPacabana cable robot, demonstrating the feasibility of adaptively adjusting cable preloads during platform motion and object manipulation.
- The results show that the geometric stiffness of the platform can be adaptively adjusted without significant loss of pose accuracy compared to conventional position-controlled operation.
Stats
The cable robot COPacabana has a platform mass of 13.9 kg and a payload of 15.2 kg.
The target path velocity during the experiments was 0.34 m/s.
The cable force limits were set to 50 N minimum and 700 N maximum.
Quotes
"The presented method allows an operator to increase the stiffness of the platform if required when loading and unloading objects. In contrast, the stiffness of the platform and the energy consumption for valid force distribution can be reduced by the operator, respectively."
"Finally, it is shown that the preload of the cables can be adaptively changed during platform motion and during manipulation of an additional object without changes of the platform pose."