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Academic OrganizationTEL
Education and Research OrganizationFaculty of EngineeringFAX
PositionSenior Assistant ProfessorMail Address
Address4-17-1, Wakasato, Nagano City 380-8553Web site


Research Field
Artificial Intelligence
Academic Background
Graduate School
Nagoya University , (Complex Systems Science , Graduate School of Information Science) , 2015
Utrecht University , (Cognitive Artificial Intelligence , Graduate School of Natural Sciences) , 2010

Utrecht University , (Faculty of Humanities) , 2007

PhD (Information Science) , Nagoya University (Japan)
BSc , Utrecht University (The Netherlands)
Research Career
Research Career
2015-2017 , Researcher (Shinshu University, Department of Engineering)
2013-2015 , JSPS Research Fellow (DC2)


Books, Articles, etc.
Disaster Robotics -Results from the ImPACT Tough Robotics Challenge-Chapter: Cyber-Enhanced Rescue Canine
Springer 2019(Jan.)
Author:Kazunori Ohno, Ryunosuke Hamada, Tatsuya Hoshi, Hiroyuki Nishinoma, Shumpei Yamaguchi, Solvi Arnold, Kimitoshi Yamazaki

An image recognition system aimed at search activities using cyber search and rescue dogs
Journal of Field Robotics,36(4):677-695 2018(Dec. 03)
Author:Solvi Arnold, Kazunori Ohno, Ryunosuke Hamada, Kimitoshi Yamazaki

EM*D-net による動作生成と形状予測に基づく布製品の操作
日本機械学会論文集,84(864) 2018(Aug. 25)

画像ラボ,29(2):7-14 2018(Feb.)
Author:山崎公俊,Solvi Arnold

Unfolding of a rectangular cloth from unarranged starting shapes by a Dual-Armed robot with a mechanism for managing recognition error and uncertainty
Advanced Robotics, Vol.31, Issue 10, pp. 544 – 556,,31(10):544-556 2017(Feb. 09)
Author:Hiroyuki Yuba, Solvi Arnold, Kimitoshi Yamazaki
Abstract:We propose a method for unfolding a rectangular cloth placed on a table in an arbitrary unarranged shape, using a dual arm robot. There are many situations where the manipulation of fabric products by dual arm robots is slow due to operation complexity. Also, observation of fabric products in unarranged shapes can be fraught with uncertainty, posing further difficulties for robotic manipulation. In this article, we address these problems for our specific task, implementing a ‘pinch and slide motion’ to address the former issue, and an operation selection mechanism implemented as a partially observable Markov decision process to address the latter. We used this approach to let a robot unfold a rectangular cloth, thereby experimentally verifying the effectiveness of our approach.
Keywords:Cloth unfolding, dual-armed manipulation, pinch and slide motion

An Object Recognition System for Disaster Robotics – UI Design and Platform Integration –
日本ロボット学会 , 第36回日本ロボット学会学術講演会 RSJ2018 2018(Sep. 05)
Author:Solvi Arnold, Kimitoshi Yamazaki:

A Neural Network Approach for Fast and Flexible Multi-Step Cloth Manipulation Planning
Third Machine Learning in Planning and Control of Robot Motion Workshop at ICRA2018 2018(May)
Author:Solvi Arnold, Kimitoshi Yamazaki

Cloth Manipulation Planning by Back-propagationusing a 3D Convolutional Auto-Encoder and aRecurrent Neural Network
日本ロボット学会 , 第35回日本ロボット学会学術講演会 2017(Sep. 13)
Author:Solvi Arnold, 山崎公俊

Hanging Work of T-Shirt in Consideration of Deformability and Stretchability
IEEE International Conference on Information and Automation 2017(Jul. 18)
Author:Yosuke Koishihara, Solvi Arnold, Kimitoshi Yamazaki, Takamitsu Matsubara

Real-time scene parsing by means of a convolutional neural network for mobile robots in disaster scenarios
IEEE International Conference on Information and Automation , :201-207 2017(Jul. 18)
Author:Solvi Arnold, Kimitoshi Yamazaki
Abstract:Disaster robotics poses particular challenges for computer vision, both in terms of image characteristics (due to motion blur, difficult light conditions, lack of up/down orientation, etc.), and in terms of learning data (limited availability, difficulty of annotation due to image quality, etc.). We developed a system for real-time scene-parsing, intended for use in a support system for operators of remote-controlled mobile robots employed in disaster areas. Our testbed is video footage gathered by a snake-like mobile robot exploring an (artificial) collapsed building environment. The core of the system is a relatively small-scale convolutional neural network. Our approach combines pixel-level learning with superpixel-level classification, in an effort to learn efficiently from a relatively small number of partially annotated frames. Our classification system is capable of real-time operation, and demonstrates that convolutional neural networks can be applied effectively even under the harsh conditions imposed by disaster robotics
Keywords:disaster robotics, rescue robots, computer vision, convolutional neural networks, scene parsing

ロボティクス・メカトロニクス講演会2017 2017(May 12)
Author:山崎公俊,松田耕太郎,Solvi Arnold,星達也,山口竣平,濱田龍之介,大野和則

Implicit Policies for Deformable Object Manipulation with Arbitrary Start and End States: A Novel Evolutionary Approach
2016 IEEE Conference on Robotics and Biomimetics , :1776 -1781 2016(Dec. 06)
Author:Solvi Arnold, Kimitoshi Yamazaki

第22回ロボティクスシンポジア , :211-212 2016(Mar. 16)
Author:Arnold Solvi, 山崎公俊

Unfolding of a Rectangular Cloth Based on Action Selection Depending on Recognition Uncertainty
IEEE/SICE International Symposium on System Integration , :623 – 628 2015(Dec.)
Author:Hiroyuki Yuba, Solvi Arnold, Kimitoshi Yamazaki