Parallel Transmission Aware Co-Design: Enhancing Manipulator Performance Through Actuation-Space Optimization
Paper in proceeding, 2025

In robotics, structural design and behavior optimization have long been considered separate processes, resulting in the development of systems with limited capabilities. Recently, co-design methods have gained popularity, where bi-level formulations are used to simultaneously optimize the robot design and behavior for specific tasks. However, most implementations assume a serial or tree-type model of the robot, overlooking the fact that many robot platforms incorporate parallel mechanisms. In this paper, we present a first co-design formulation that explicitly incorporates parallel coupling constraints into the dynamic model of the robot. In this framework, an outer optimization loop focuses on the design parameters, in our case the transmission ratios of a parallel belt-driven manipulator, which map the desired torques from the joint space to the actuation space. An inner loop performs trajectory optimization in the actuation space, thus exploiting the entire dynamic range of the manipulator. We compare the proposed method with a conventional co-design approach based on a simplified tree-type model. By taking advantage of the actuation space representation, our approach leads to a significant increase in dynamic payload capacity compared to the conventional co-design implementation.

Author

Rohit Kumar

Deutsches Forschungszentrum fur Kunstliche Intelligenz

Melya Boukheddimi

Deutsches Forschungszentrum fur Kunstliche Intelligenz

Dennis Mronga

Deutsches Forschungszentrum fur Kunstliche Intelligenz

Shivesh Kumar

Deutsches Forschungszentrum fur Kunstliche Intelligenz

Chalmers, Mechanics and Maritime Sciences (M2), Dynamics

Frank Kirchner

Universität Bremen

Deutsches Forschungszentrum fur Kunstliche Intelligenz

IEEE International Conference on Intelligent Robots and Systems

21530858 (ISSN) 21530866 (eISSN)

1171-1177
9798331543938 (ISBN)

2025 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2025
Hangzhou, China,

Subject Categories (SSIF 2025)

Robotics and automation

Control Engineering

DOI

10.1109/IROS60139.2025.11246203

More information

Latest update

2/20/2026