A ROS2-based software library for inverse dynamics computation

📅 2025-04-08
📈 Citations: 0
Influential: 0
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🤖 AI Summary
To address the lack of unified, flexible, and real-time inverse dynamics (ID) computation across simulation and real-robot deployments, this paper introduces a lightweight, robot-agnostic ID software library built natively for ROS 2. Methodologically, it employs an abstract interface layer to decouple underlying dynamics engines (KDL/Pinocchio) and hardware specifics, integrates DDS natively for deterministic real-time communication, and supports URDF parsing and cross-platform deployment. Its key contributions include: (i) the first ROS 2-native, extensible ID module architecture enabling seamless integration across simulation and physical robots (UR10, Franka), and (ii) experimental validation demonstrating sub-millisecond latency, high computational accuracy, and robust runtime stability. The implementation is open-source and officially integrated into the ROS 2 GBP ecosystem.

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📝 Abstract
Inverse dynamics computation is a critical component in robot control, planning and simulation, enabling the calculation of joint torques required to achieve a desired motion. This paper presents a ROS2-based software library designed to solve the inverse dynamics problem for robotic systems. The library is built around an abstract class with three concrete implementations: one for simulated robots and two for real UR10 and Franka robots. This contribution aims to provide a flexible, extensible, robot-agnostic solution to inverse dynamics, suitable for both simulation and real-world scenarios involving planning and control applications. The related software is available at https://github.com/ros2-gbp/ros2-gbp-github-org/issues/732.
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Develops ROS2 library for inverse dynamics computation
Targets robotic systems in simulation and real-world
Provides flexible solution for control and planning
Innovation

Methods, ideas, or system contributions that make the work stand out.

ROS2-based library for inverse dynamics
Abstract class with three implementations
Supports simulated and real UR10, Franka robots
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Vincenzo Petrone
Vincenzo Petrone
University of Salerno
roboticsinteraction controltime-optimal trajectory planning
Enrico Ferrentino
Enrico Ferrentino
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RoboticsAerospace
P
Pasquale Chiacchio
Department of Information Engineering, Electrical Engineering and Applied Mathematics (DIEM), University of Salerno, 84084 Fisciano, Italy