Citation: Yi, J.-s.; Luong, T.A.; Chae,
H.; Ahn, M.S.; Noh, D.; Tran, H.N.;
Doh, M.; Auh, E.; Pico, N.; Yumbla, F.;
et al. An Online Task-Planning
Framework Using Mixed Integer
Programming for Multiple Cooking
Tasks Using a Dual-Arm Robot. Appl.
Sci. 2022, 12, 4018. https://doi.org/
10.3390/app12084018
Academic Editors: Giovanni
Boschetti and João Miguel da Costa
Sousa
Received: 15 March 2022
Accepted: 11 April 2022
Published: 15 April 2022
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Article
An Online Task-Planning Framework Using Mixed Integer
Programming for Multiple Cooking Tasks Using a
Dual-Arm Robot
June-sup Yi
1
, Tuan Anh Luong
1
, Hosik Chae
2
, Min Sung Ahn
2
, Donghun Noh
2
, Huy Nguyen Tran
1
,
Myeongyun Doh
1
, Eugene Auh
1
, Nabih Pico
1,3
, Francisco Yumbla
1
, Dennis Hong
2
and Hyungpil Moon
1,
*
1
Mechanical Engineering, Sungkyunkwan University, Seobu-ro, Suwon-si 2066, Korea;
caro33@g.skku.edu (J.-s.Y.); luongtuan@g.skku.edu (T.A.L.); hntran@g.skku.edu (H.N.T.);
ehauddbs@g.skku.edu (M.D.); egauh@g.skku.edu (E.A.); npico@g.skku.edu (N.P.);
fryumbla@g.skku.edu (F.Y.)
2
Mechanical and Aerospace Engineering, University of California, Los Angeles, CA 90095, USA;
hosikchae@ucla.edu (H.C.); aminsung@ucla.edu (M.S.A.); dhnoh0820@ucla.edu (D.N.);
dennishong@ucla.edu (D.H.)
3
Facultad de Ingeniería en Electricidad y Computación, Escuela Superior Politécnica del Litoral, ESPOL,
Campus Gustavo Galindo, Guayaquil 09-01-5863, Ecuador
* Correspondence: hyungpil@g.skku.edu
Abstract:
This work proposes an online task-scheduling method using mixed-integer programming
for a multi-tasking problem regarding a dual-arm cooking robot in a controlled environment. Given
each task’s processing time, their location in the working space, dependency, the required number
of arms, and the kinematic constraints of the dual-arm robot, the proposed optimization algorithm
can produce a feasible solution to scheduling the cooking order for each task and for each associated
arms so that the total cooking time and the total moving distance for each arm are minimized. We
use a subproblem optimization strategy in which the number of tasks to be planned is divided into
several groups instead of planning all tasks at the same time. By doing so, the planning time can be
significantly decreased, making the algorithm practical for online implementation. The feasibility of
our optimization method and the effectiveness of the subproblem optimization strategy were verified
through simulated experiments consisting of 30 to 120 tasks. The results showed that our strategy is
advantageous in terms of computation time and makespan for large problems.
Keywords: mixed integer programming; cooking robot; dual-arm robot; task planning; task scheduling
1. Introduction
Currently, autonomous robotic systems are used in various processes in manufacturing.
In the food industry, robotic systems are mainly used for food processing and packaging in
mass-production plants [
1
], while cooking and meal preparation at home or in restaurants
is one of the least automated areas. In restaurants that offer a variety of choices on their
menu, efficient job assignments are critical to serving orders on time as task scheduling
greatly affects efficiency [2].
Attempts have been made to automate cooking tasks using robots. Cooking motions,
such as cutting and peeling vegetables [
3
], mixing and chopping [
4
], and rocking and
flipping of pans [
5
], have been studied using robots. Another research [
6
] proposes the
collaboration of two robots to cook, but is limited to making a single type of dish. In
general, to make a recipe executable by a robot, the recipe has to be decomposed into
sub-tasks. In the case of simple recipes, the order of operation can be specified by breaking
down a written recipe into keywords, and the robot could cook according to the recipes [
4
].
However, for more complicated recipes, such as those with verbose descriptions, including
Appl. Sci. 2022, 12, 4018. https://doi.org/10.3390/app12084018 https://www.mdpi.com/journal/applsci
