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Robodimm: A Physics-Grounded Framework for Automated Actuator Sizing in Scalable Modular Robots

J. L. Torres, M. Munoz, J. D. Alvarez, J. L. Blanco, A. Gimenez

TL;DR

Robodimm, a software framework for automated actuator sizing in scalable robot architectures, uses a Karush-Kuhn-Tucker (KKT) formulation for constrained inverse dynamics and leverages Pinocchio for dynamics and Pink for inverse kinematics.

Abstract

Selecting an appropriate motor-gearbox combination is a critical design task in robotics because it directly affects cost, mass, and dynamic performance. This process is especially challenging in modular robots with closed kinematic chains, where joint torques are coupled and actuator inertia propagates through the mechanism. We present Robodimm, a software framework for automated actuator sizing in scalable robot architectures. By leveraging Pinocchio for dynamics and Pink for inverse kinematics, Robodimm uses a Karush-Kuhn-Tucker (KKT) formulation for constrained inverse dynamics. The platform supports parametric scaling, interactive trajectory programming through jog modes, and a two-round validation workflow that addresses actuator self-weight effects.

Robodimm: A Physics-Grounded Framework for Automated Actuator Sizing in Scalable Modular Robots

TL;DR

Robodimm, a software framework for automated actuator sizing in scalable robot architectures, uses a Karush-Kuhn-Tucker (KKT) formulation for constrained inverse dynamics and leverages Pinocchio for dynamics and Pink for inverse kinematics.

Abstract

Selecting an appropriate motor-gearbox combination is a critical design task in robotics because it directly affects cost, mass, and dynamic performance. This process is especially challenging in modular robots with closed kinematic chains, where joint torques are coupled and actuator inertia propagates through the mechanism. We present Robodimm, a software framework for automated actuator sizing in scalable robot architectures. By leveraging Pinocchio for dynamics and Pink for inverse kinematics, Robodimm uses a Karush-Kuhn-Tucker (KKT) formulation for constrained inverse dynamics. The platform supports parametric scaling, interactive trajectory programming through jog modes, and a two-round validation workflow that addresses actuator self-weight effects.
Paper Structure (13 sections, 3 figures, 2 tables)

This paper contains 13 sections, 3 figures, 2 tables.

Table of Contents

  1. Introduction
  2. System Overview
  3. Software architecture
  4. Software functionalities
  5. Graphical user interface
  6. Case Study and Experimental Evaluation
  7. Palletizing endpoint example
  8. Trajectory-based dynamic evaluation
  9. Actuator requirement extraction and selection
  10. DEMO versus PRO torque comparison
  11. Discussion and Impact
  12. Code Availability
  13. Conclusions

Figures (3)

  • Figure 1: Unified Robodimm architecture with DEMO and PRO execution paths.
  • Figure 2: Robodimm graphical interface. The layout integrates 3D visualization, jog/program tools, robot configuration, and dynamic analysis outputs in a single workspace.
  • Figure 3: CR4 palletizing case study for the final benchmark scenario (scale 1.6, payload 10 kg). Top row: actuated joint positions, velocities, and accelerations. Bottom row: DEMO/PRO torque comparison, absolute torque error, and RMS torque by joint. In the torque panel, J1--J3 use the left axis and J4 uses the right axis.