MAEDA Lab

INTELLIGENT & INDUSTRIAL ROBOTICS

Maeda Lab: 2023–2024

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 (2023–2024 Academic Year)

• Dr. Yusuke MAEDA (Professor, Div. of Systems Research, Fac. of Engineering)

• 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)

– Haruki KAMIKUKITA

– Kenta SAKAKI

– Mizuki SHONO

– Itsuma MATSUI

– Pedro SAMAN

– Rohit THAKUR

– Honoka OKUGUCHI

– Naoya TAKAHASHI

– Shuto YAMADA

– Cheng WU

• Undergraduate Students (Mechanical Engineering Program, Dept. of Mechanical

Engineering, Materials Science, and Ocean Engineering, College of Engineering Science)

– Rion SATO

– Kazuhiro KURIHARA

– Masato KONISHI

– Shoma SUGISAWA

– Hiroki TABATA

2023–2024 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

2023–2024 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 (Fig. 5). The system also supports the above robot program-

ming with manual volume sweeping [4]. Another support system for online robot programming

is also developed. In this system, it is possible to group and move existing teaching 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: A Robot Programming System Based on ROS/MoveIt Utilizing AR: Im-

plementation of Motion Planning Function Based on Volume Sweeping, Proc. of SICE 23rd Conf. on

System Integration (SI2022), pp. 994–998, 2022 (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