TY - GEN
T1 - Going Green with Lightweight Robots
T2 - Energy Optimal Programming of Lightweight Robots
AU - Heredia, Juan
AU - Schlette, Christian
AU - Kjærgaard, Mikkel Baun
PY - 2023
Y1 - 2023
N2 - Industries worldwide are shifting their focus toward implementing sustainable practices. Robotics technology has become essential in this transformation due to its ability to enhance productivity and precision while minimizing material and energy waste. Lightweight industrial robots (LIRs), also known as collaborative robots (cobots), have gained significance for their cooperative and efficient work with human operators. This study explores energy optimization techniques tailored specifically for LIRs. Unlike conventional industrial robots (IRs), LIRs have unique energy characteristics, requiring unique optimization strategies. We introduce three energy-minimizing techniques for LIRs: optimal manufacturer commands, optimal motion time determination, and dissipative energy reduction. Each technique can significantly impact the energy efficiency of LIRs. Case studies demonstrate that these strategies can result in energy savings of up to 31\% for a manipulator. This study contributes to the advancement of energy-optimized industrial robotics, providing valuable insights for enhancing sustainability in modern manufacturing environments.
AB - Industries worldwide are shifting their focus toward implementing sustainable practices. Robotics technology has become essential in this transformation due to its ability to enhance productivity and precision while minimizing material and energy waste. Lightweight industrial robots (LIRs), also known as collaborative robots (cobots), have gained significance for their cooperative and efficient work with human operators. This study explores energy optimization techniques tailored specifically for LIRs. Unlike conventional industrial robots (IRs), LIRs have unique energy characteristics, requiring unique optimization strategies. We introduce three energy-minimizing techniques for LIRs: optimal manufacturer commands, optimal motion time determination, and dissipative energy reduction. Each technique can significantly impact the energy efficiency of LIRs. Case studies demonstrate that these strategies can result in energy savings of up to 31\% for a manipulator. This study contributes to the advancement of energy-optimized industrial robotics, providing valuable insights for enhancing sustainability in modern manufacturing environments.
KW - Energy and Environment-Aware Automation
KW - Industrial Robots
KW - Task and Motion Planning
U2 - 10.1109/ICAR58858.2023.10406598
DO - 10.1109/ICAR58858.2023.10406598
M3 - Article in proceedings
SP - 212
EP - 219
BT - 2023 21st International Conference on Advanced Robotics, ICAR 2023
ER -