Model-Based Robotic Manipulation of Thin Objects: Strategies for High-Precision Placement

Kaydedildi:
Detaylı Bibliyografya
Yayımlandı:PQDT - Global (2025)
Yazar: Dai, Zhenjiu
Baskı/Yayın Bilgisi:
ProQuest Dissertations & Theses
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Online Erişim:Citation/Abstract
Full Text - PDF
Full text outside of ProQuest
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100 1 |a Dai, Zhenjiu 
245 1 |a Model-Based Robotic Manipulation of Thin Objects: Strategies for High-Precision Placement 
260 |b ProQuest Dissertations & Theses  |c 2025 
513 |a Dissertation/Thesis 
520 3 |a Robotic object placement constitutes a critical component of pick-and-place operation. While significant advancements have been made in grasp planning and object acquisition strategies, the subsequent phase of safely depositing objects - particularly those with thin profiles or complex material properties - remains an open research problem. This dissertation bridges this gap by introducing model-based manipulation frameworks tailored for the precise placement of thin-rigid and deformable linear objects (DLOs), addressing both theoretical and practical challenges in robotic manipulation.First, we present a closed-loop system designed for handling thin-rigid objects, which are prone to damage during placement due to their mechanical brittleness. The system integrates vision-based tactile sensors with pixel-level resolution and soft-contact capabilities, enabling real-time perception of interaction dynamics. A motion controller processes this sensory feedback to execute optimized in-hand rotation and sliding maneuvers, ensuring stable and damagefree placement on target surfaces. Second, we develop an open-loop framework for deformable linear objects, where the primary challenge lies in controlling infinite-degree-of-freedom systems with limited actuation points. Our method analytically relates object deformation to boundary constraint forces, enabling global shape control via a single grasp point. This approach achieves curvature matching with target surfaces without requiring full-state feedback.The proposed techniques are object-agnostic and dimensionally scalable. Real-world experimental validation confirms their efficacy and robustness across industrial and domestic applications, diverse object classes, and varying environmental conditions. 
653 |a Kinematics 
653 |a Control algorithms 
653 |a Adaptability 
653 |a Planning 
653 |a Systems design 
653 |a Robots 
653 |a Data processing 
653 |a Physical properties 
653 |a Geometry 
653 |a Advanced materials 
653 |a Robotics 
653 |a Aerospace engineering 
653 |a Mechanical engineering 
773 0 |t PQDT - Global  |g (2025) 
786 0 |d ProQuest  |t ProQuest Dissertations & Theses Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3273641178/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3273641178/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u https://doi.org/10.14711/thesis-hdl152549