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Energy Consumption in Robotics: A Simplified Modeling Approach

Valentyn Petrichenko, Lisa Lokstein, Gregor Thiele, Kevin Haninger

TL;DR

This work proposes an approach that uses differentiable inertial and kinematic models from standard open-source tools, integrating with standard ROS planning methods, and compares the inertial and electrical models on a collaborative robot, showing that simplified models provide competitive accuracy and are easier to deploy in practice.

Abstract

The energy use of a robot is trajectory-dependent, and thus can be reduced by optimization of the trajectory. Current methods for robot trajectory optimization can reduce energy up to 15\% for fixed start and end points, however their use in industrial robot planning is still restricted due to model complexity and lack of integration with planning tools which address other concerns (e.g. collision avoidance). We propose an approach that uses differentiable inertial and kinematic models from standard open-source tools, integrating with standard ROS planning methods. An inverse dynamics-based energy model is optionally extended with a single-parameter electrical model, simplifying the model identification process. We compare the inertial and electrical models on a collaborative robot, showing that simplified models provide competitive accuracy and are easier to deploy in practice.

Energy Consumption in Robotics: A Simplified Modeling Approach

TL;DR

This work proposes an approach that uses differentiable inertial and kinematic models from standard open-source tools, integrating with standard ROS planning methods, and compares the inertial and electrical models on a collaborative robot, showing that simplified models provide competitive accuracy and are easier to deploy in practice.

Abstract

The energy use of a robot is trajectory-dependent, and thus can be reduced by optimization of the trajectory. Current methods for robot trajectory optimization can reduce energy up to 15\% for fixed start and end points, however their use in industrial robot planning is still restricted due to model complexity and lack of integration with planning tools which address other concerns (e.g. collision avoidance). We propose an approach that uses differentiable inertial and kinematic models from standard open-source tools, integrating with standard ROS planning methods. An inverse dynamics-based energy model is optionally extended with a single-parameter electrical model, simplifying the model identification process. We compare the inertial and electrical models on a collaborative robot, showing that simplified models provide competitive accuracy and are easier to deploy in practice.

Paper Structure

This paper contains 10 sections, 10 equations, 4 figures, 1 table.

Table of Contents

  1. Introduction
  2. Dynamic robot models
  3. Mechanical model
  4. Electrical model
  5. Trajectory energy
  6. Power model
  7. Full power profile
  8. Trajectory
  9. Validation
  10. Conclusions

Figures (4)

  • Figure 1: Overview of the proposed energy modeling pipeline, using standardized data formats for robot model and task, open-source trajectory planning methods, and being validated with energy measurements on robot execution.
  • Figure 2: Least Square Identification of Electrical Parameter for Method 2
  • Figure 3: Comparison of two Modeling Methods on the Franka Emika Robot
  • Figure 4: Visualized Comparison of Modeling Methods on the Franka Emika Robot