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

TL;DR

Robodimm is a physics-based software framework that automates actuator sizing for scalable modular robots, considering dynamics, kinematic coupling, and self-weight effects to optimize design choices.

Contribution

It introduces a novel KKT-based constrained inverse dynamics approach integrated with parametric scaling and validation workflows for modular robot actuator selection.

Findings

Effective automated actuator sizing for complex modular robots

Supports interactive trajectory programming and validation workflows

Addresses self-weight effects in actuator design

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.