TY - GEN
T1 - Impact force minimization algorithm for collaborative robots using impact force prediction model
AU - Kim, Tae Jung
AU - Kim, Ji Hoon
AU - Ahn, Kuk Hyun
AU - Song, Jae Bok
N1 - Funding Information:
This research was supported by the MOTIE under the Industrial Foundation Technology Development Program supervised by the KEIT (No. 20008613)
Publisher Copyright:
© 2020 Institute of Control, Robotics, and Systems - ICROS.
PY - 2020/10/13
Y1 - 2020/10/13
N2 - Recently, the demand for collaborative robots is increasing in the industrial field. However, as the collaborative robots share the same workspace with human workers, there is a high possibility of collision between the robot and the worker. A possible method to ensure the safety of a human worker is to restrict the impact force that the robot exerts on the worker during a collision. That is, if the impact force can be predicted, the robot motion that causes excessive impact force can be detected and handled properly before the actual robot motion. To this end, an algorithm for predicting the impact force generated by a collision is proposed, and a method for ensuring the human safety, by modifying the trajectory of the robot when the excessive impact is predicted with current motion, is investigated. To establish the impact force prediction model, collision experiments were performed with a 6-DOF collaborative robot and a dummy. Moreover, an algorithm for minimizing the impact force, by reducing the end-effector velocity of the robot when excessive impact is predicted from the established model, is proposed to ensure the human safety. The performance of the algorithm was verified through various experiments.
AB - Recently, the demand for collaborative robots is increasing in the industrial field. However, as the collaborative robots share the same workspace with human workers, there is a high possibility of collision between the robot and the worker. A possible method to ensure the safety of a human worker is to restrict the impact force that the robot exerts on the worker during a collision. That is, if the impact force can be predicted, the robot motion that causes excessive impact force can be detected and handled properly before the actual robot motion. To this end, an algorithm for predicting the impact force generated by a collision is proposed, and a method for ensuring the human safety, by modifying the trajectory of the robot when the excessive impact is predicted with current motion, is investigated. To establish the impact force prediction model, collision experiments were performed with a 6-DOF collaborative robot and a dummy. Moreover, an algorithm for minimizing the impact force, by reducing the end-effector velocity of the robot when excessive impact is predicted from the established model, is proposed to ensure the human safety. The performance of the algorithm was verified through various experiments.
KW - Collaborative robot
KW - Collision safety
KW - Impact
UR - http://www.scopus.com/inward/record.url?scp=85098059971&partnerID=8YFLogxK
U2 - 10.23919/ICCAS50221.2020.9268300
DO - 10.23919/ICCAS50221.2020.9268300
M3 - Conference contribution
AN - SCOPUS:85098059971
T3 - International Conference on Control, Automation and Systems
SP - 869
EP - 872
BT - 2020 20th International Conference on Control, Automation and Systems, ICCAS 2020
PB - IEEE Computer Society
T2 - 20th International Conference on Control, Automation and Systems, ICCAS 2020
Y2 - 13 October 2020 through 16 October 2020
ER -