MAEDA Lab
MAEDA Lab
INTELLIGENT & INDUSTRIAL ROBOTICS
Maeda Lab: 2022–2023
Div. of Systems Research, Faculty of Engineering / Specialization in Mechanical Engineering, Dept. of
Mechanical Engineering, Materials Science, and Ocean Engineering, Graduate School of Engineering Science /
Interfaculty Graduate School of Innovative and Practical Studies /
Dept. of Mechanical Engineering, Materials Science, and Ocean Engineering, College of Engineering Science,
Yokohama National University
Mechanical Engineering and Materials Science Bldg. (N6-5),
79-5 Tokiwadai, Hodogaya-ku, Yokohama, 240-8501 JAPAN
Tel/Fax +81-45-339-3918 (Prof. Maeda)/+81-45-339-3894 (Lab)
E-mail maeda[at]ynu.ac.jp
https://iir.ynu.ac.jp/
People (2022–2023 Academic Year)
Dr. Yusuke MAEDA (Professor, Div. of Systems Research, Fac. of Engineering)
Doctoral Students (Specialization in Mechanical Engineering, Dept. of Mechanical
Engineering, Materials Science, and Ocean Engineering, Graduate School of Engineering
Science)
Reiko TAKAHASHI (JSPS Research Fellow)
Master’s Students (Specialization in Mechanical Engineering, Dept. of Mechanical
Engineering, Materials Science, and Ocean Engineering, Graduate School of Engineering
Science/Interfaculty Graduate School of Innovative and Practical Studies)
Akitoshi SAKATA
Akihide SUGA
Naruya SUZUKI
Kenta TAKAHASHI
Yuta NAKANISHI
Yoshiki TAHARA
Haruki KAMIKUKITA
Kenta SAKAKI
Mizuki SHONO
Itsuma MATSUI
Pedro SAMAN
Undergraduate Students (Mechanical Engineering Program, Dept. of Mechanical
Engineering, Materials Science, and Ocean Engineering, College of Engineering Science)
Fumiya ENDO
Rion SATO
Naoya TAKAHASHI
Shogo MIKAMI
2022–2023 Maeda Lab, Yokohama National University
SLAM-Integrated Kinematic Calibration (SKCLAM)
SLAM (Simultaneous Localization and Mapping) techniques can be applied to industrial manip-
ulators for 3D mapping around them and calibration of their kinematic parameters. We call this
“SKCLAM” (Simultaneous Kinematic Calibration, Localization and Mapping). Using an RGB-
D camera attached to the end-effector of a manipulator (Fig. 1), we demonstrated successful
SKCLAM in a virtual environment (Fig. 2) and a real environment (Fig. 3) [1][2]. We are also
studying SKCLAM with spherical cameras [3] and stereo cameras [4].
References
[1] J. Li, A. Ito, H. Yaguchi and Y. Maeda: Simultaneous kinematic calibration, localization, and mapping
(SKCLAM) for industrial robot manipulators, Advanced Robotics, Vol. 33, No. 23, pp. 1225–1234, 2019.
[2] A. Ito, J. Li and Y. Maeda: SLAM-Integrated Kinematic Calibration Using Checkerboard Patterns, Proc.
of 2020 IEEE/SICE Int. Symp. on System Integration (SII 2020), pp. 551–556, 2020.
[3] Y. Tanaka, J. Li, A. Ito and Y. Maeda: SLAM-Integrated Kinematic Calibration with Spherical Cameras
for Industrial Manipulators, Proc. of JSME Conf. on Robotics and Mechatronics 2020 (ROBOMECH
2020), 2P2-B05, 2020 (in Japanese).
[4] Y. Nagatomo, J. Li, Y. Tanaka and Y. Maeda: SLAM-integrated Kinematic Calibration with a Stereo
Camera for Industrial Robots, Proc. of JSME Conf. of Manufacturing Systems Division 2021, pp. 77–
78, 2021 (in Japanese).
Fig. 1 Manipulator Equipped
with an RGB-D Camera
Fig. 2 SKCLAM in Virtual Environment
Fig. 3 Example of an Obtained 3D Map
2
2022–2023 Maeda Lab, Yokohama National University
Robot Teaching
Teaching is indispensable for current industrial robots to execute tasks. Human operators have to
teach motions in detail to robots by, for example, conventional teaching/playback. However, robot
teaching is complicated and time-consuming for novice operators and the cost for training them
is often unaffordable in small-sized companies. Thus we are studying easy robot programming
methods toward the dissemination of robot utilization.
Robot programming with manual volume sweeping We developed a robot programming
method for part handling [1][2]. In this method, a human operator makes a robot manipulator
sweep a volume by its bodies. The swept volume stands for (a part of) the manipulator’s free
space, because the manipulator has passed through the volume without collisions. Next, the
obtained swept volume is used by a motion planner to generate a well-optimized path of the
manipulator automatically. The swept volume can be displayed with Augmented Reality (AR)
so that human operators can easily understand it, which leads to efficient robot programming
[3] (Fig. 4).
Assisting Online Robot Programming We are developing a support system for online robot
programming using an optical see-through AR device that can overlay useful information on
a real robot such as its movable area [4] (Fig. 5). Another support system for online robot
programming is also developed. In this system, it is possible to group and move existing teach-
ing points, and generate robot motions that connect the points. This is useful for adaptation to
product specification changes in robotic assembly [5].
References
[1] Y. Maeda, T. Ushioda and S. Makita: Easy Robot Programming for Industrial Manipulators by Manual
Volume Sweeping, Proc. of 2008 IEEE Int. Conf. on Robotics and Automation (ICRA 2008), pp. 2234–
2239, 2008.
[2] S. Ishii and Y. Maeda: Programming of Robots Based on Online Computation of Their Swept Vol-
umes, Proc. of 23rd IEEE Int. Symp. on Robot and Human Interactive Communication (RO-MAN 2014),
pp. 385–390, 2014.
[3] Y. Sarai and Y. Maeda: Robot Programming for Manipulators through Volume Sweeping and Augmented
Reality, Proc. of 13th IEEE Conf. on Automation Science and Engineering (CASE 2017), pp. 302–307,
2017.
[4] K. Takahashi and Y. Maeda: Implementation and Evaluation of a System for Robot Teaching Support
Using an Optical See-Through AR Device, Proc. of 2021 JSME Conf. on Robotics and Mechatronics
(ROBOMECH 2021), 2P3-A02, 2021 (in Japanese).
[5] H. Ihara and Y. Maeda: A Robot Programming System with Teach Point Manipulation and Motion Plan-
ning to Adapt Product Specification Change, Proc. of SICE 22nd Conf. on System Integration (SI2021),
pp. 3263–3267, 2021 (in Japanese).
Fig. 4 AR Display of Swept Volume and Planned Path
Fig. 5 AR Display of Movable
Area with Fixed Gripper Pose
3