Solvi Arnold

Shinshu University, Nagano University

Papers

14

Total Citations

222

H-Index

7

About

Solvi Arnold is a leading researcher in robotic manipulation of deformable objects, with a particular focus on cloth and cable handling. His work addresses fundamental challenges in enabling robots to perceive, plan, and execute tasks involving materials that change shape unpredictably. Arnold’s major contributions include the development of the Encode–Manipulate–Decode (EMD) Net, a motion planning framework for cloth manipulation that has garnered 65 citations, and a disruption-resistant manipulation system that integrates online shape estimation and trajectory correction to handle mid-task disturbances. His research also extends to disaster robotics, where he has developed continuum robots with distributed sensors for search and rescue (45 citations) and cyber-enhanced rescue canines. Arnold’s work on dual-armed robotic unfolding of cloth from unarranged starting shapes (39 citations) demonstrates his ability to manage recognition errors and uncertainty. With over 200 total citations across his top papers, Arnold has made significant strides in making deformable object manipulation more robust and practical for real-world applications, from household tasks to industrial wiring and disaster response.

Research Focus

Key Achievements

7
H-Index
14
Papers
222
Total Citations
16
Avg Citations/Paper
🏆 Most Cited Paper
EMD Net: An Encode–Manipulate–Decode Network for Cloth Manipulation
65 citations · 2018
📈 Most Prolific Year: 2017 (3 Papers)
🤝 Key Collaborators: 51
🏛 Institutions: Shinshu University, Nagano University

Top Papers

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  5. 5
    Cyber-Enhanced Rescue Canine
    11 citations · 2019
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago