TY - GEN
T1 - Planning algorithms for multi-setup multi-pass robotic cleaning with oscillatory moving tools
AU - Kabir, Ariyan M.
AU - Langsfeld, Joshua D.
AU - Shriyam, Shaurya
AU - Rachakonda, Vinaichandra Sai
AU - Zhuang, Cunbo
AU - Kaipa, Krishnanand N.
AU - Marvel, Jeremy
AU - Gupta, Satyandra K.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/14
Y1 - 2016/11/14
N2 - We present planning algorithms for cleaning stains on a curved object. Removing the stain may require multiple reorientations and repositions of the object and some portions of the stain may require multiple cleaning passes. The experimental setup involves two robot arms. The first arm immobilizes the object. The second arm moves the cleaning tool. The algorithm analyzes the stain and determines the sequence of positions and orientations needed to clean the part based on the kinematic constraints of the robot arm. Our algorithm uses a depth-first branch-and-bound search to generate setup plan solutions. We also compute the cleaning trajectories and select the cleaning parameters to maximize the cleaning performance. The algorithm generates multi-pass trajectories by replanning based on the observed cleaning performance. Numerical simulations and cleaning experiments with two Kuka1 robots are used to validate our approach.
AB - We present planning algorithms for cleaning stains on a curved object. Removing the stain may require multiple reorientations and repositions of the object and some portions of the stain may require multiple cleaning passes. The experimental setup involves two robot arms. The first arm immobilizes the object. The second arm moves the cleaning tool. The algorithm analyzes the stain and determines the sequence of positions and orientations needed to clean the part based on the kinematic constraints of the robot arm. Our algorithm uses a depth-first branch-and-bound search to generate setup plan solutions. We also compute the cleaning trajectories and select the cleaning parameters to maximize the cleaning performance. The algorithm generates multi-pass trajectories by replanning based on the observed cleaning performance. Numerical simulations and cleaning experiments with two Kuka1 robots are used to validate our approach.
UR - http://www.scopus.com/inward/record.url?scp=85001060923&partnerID=8YFLogxK
U2 - 10.1109/COASE.2016.7743478
DO - 10.1109/COASE.2016.7743478
M3 - Conference contribution
AN - SCOPUS:85001060923
T3 - IEEE International Conference on Automation Science and Engineering
SP - 751
EP - 757
BT - 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016
PB - IEEE Computer Society
T2 - 2016 IEEE International Conference on Automation Science and Engineering, CASE 2016
Y2 - 21 August 2016 through 24 August 2016
ER -