TY - GEN
T1 - Labelling Lightweight Robot Energy Consumption
T2 - 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
AU - Heredia, Juan
AU - Kirschner, Robin Jeanne
AU - Schlette, Christian
AU - Abdolshah, Saeed
AU - Haddadin, Sami
AU - Kjaergaard, Mikkel Baun
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Compliance with global guidelines for sustainable and responsible production in modern industry requires a comparative analysis of consumer devices' energy consumption (EC). This also holds true for the newly established generation of lightweight industrial robots (LIRs). To identify potential strategies for energy optimization, standardized benchmarking procedures are required. However, to the best of the authors' knowledge, there is currently no standardized method for benchmarking the EC of manipulators. In response to this need, we have developed a comprehensive benchmarking framework to evaluate the EC of various LIR designs, delving into the theoretical power consumption under both static and dynamic conditions. Our analysis has led to the proposal of seven proposed metrics - three static and four dynamic. The static metrics - controller consumption, joint electronics consumption, and mechanical brakes' consumption - evaluate the maintenance EC of the robot. Meanwhile, we suggest three dynamic metrics that gauge the system's energy efficiency during motion, with or without payload. We extend this metrics selection by introducing the cost of transportation map for manipulators. For each of the metrics, we suggest a standardized measurement procedure based on state-of-the-art norms and literature. The metric set and experimental procedures are demonstrated using five manipulators (UR3e, UR5e, FR3, M0609, Gen3). Among the results, we can see interesting trends for future optimization of the electronic components and their architecture, e.g., reducing the robot's EC by decentralizing computation via low-consumption onboard controllers for basic tasks and external servers for complex ones.
AB - Compliance with global guidelines for sustainable and responsible production in modern industry requires a comparative analysis of consumer devices' energy consumption (EC). This also holds true for the newly established generation of lightweight industrial robots (LIRs). To identify potential strategies for energy optimization, standardized benchmarking procedures are required. However, to the best of the authors' knowledge, there is currently no standardized method for benchmarking the EC of manipulators. In response to this need, we have developed a comprehensive benchmarking framework to evaluate the EC of various LIR designs, delving into the theoretical power consumption under both static and dynamic conditions. Our analysis has led to the proposal of seven proposed metrics - three static and four dynamic. The static metrics - controller consumption, joint electronics consumption, and mechanical brakes' consumption - evaluate the maintenance EC of the robot. Meanwhile, we suggest three dynamic metrics that gauge the system's energy efficiency during motion, with or without payload. We extend this metrics selection by introducing the cost of transportation map for manipulators. For each of the metrics, we suggest a standardized measurement procedure based on state-of-the-art norms and literature. The metric set and experimental procedures are demonstrated using five manipulators (UR3e, UR5e, FR3, M0609, Gen3). Among the results, we can see interesting trends for future optimization of the electronic components and their architecture, e.g., reducing the robot's EC by decentralizing computation via low-consumption onboard controllers for basic tasks and external servers for complex ones.
UR - http://www.scopus.com/inward/record.url?scp=85182524814&partnerID=8YFLogxK
U2 - 10.1109/IROS55552.2023.10341484
DO - 10.1109/IROS55552.2023.10341484
M3 - Conference contribution
AN - SCOPUS:85182524814
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 1789
EP - 1796
BT - 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 1 October 2023 through 5 October 2023
ER -