Toward Dynamic Manipulation of Flexible Objects by High-Speed Robot System: From Static to Dynamic

This chapter explains dynamic manipulation of flexible objects, where the target objects to be manipulated include rope, ribbon, cloth, pizza dough, and so on. Previously, flexible object manipulation has been performed in a static or quasi-static state. Therefore, the manipulation time becomes long, and the efficiency of the manipulation is not considered to be sufficient. In order to solve these problems, we propose a novel control strategy and motion planning for achieving flexible object manipulation at high speed. The proposed strategy simplifies the flexible object dynamics. Moreover, we implemented a high-speed vision system and high-speed image processing to improve the success rate by manipulating the robot trajectory. By using this strategy, motion planning, and high-speed visual feedback, we demonstrated several tasks, including dynamic manipulation and knotting of a rope, generating a ribbon shape, dynamic folding of cloth, rope insertion, and pizza dough rotation, and we show experimental results obtained by using the high-speed robot system

UniFolding: Towards Sample-efficient, Scalable, and Generalizable Robotic Garment Folding

This paper explores the development of UniFolding, a sample-efficient, scalable, and generalizable robotic system for unfolding and folding various garments. UniFolding employs the proposed UFONet neural network to integrate unfolding and folding decisions into a single policy model that is adaptable to different garment types and states. The design of UniFolding is based on a garment's partial point cloud, which aids in generalization and reduces sensitivity to variations in texture and shape. The training pipeline prioritizes low-cost, sample-efficient data collection. Training data is collected via a human-centric process with offline and online stages. The offline stage involves human unfolding and folding actions via Virtual Reality, while the online stage utilizes human-in-the-loop learning to fine-tune the model in a real-world setting. The system is tested on two garment types: long-sleeve and short-sleeve shirts. Performance is evaluated on 20 shirts with significant variations in textures, shapes, and materials. More experiments and videos can be found in the supplementary materials and on the website: https://unifolding.robotflow.aiComment: CoRL 202

折り紙公理に基づく谷折り操作の記述・認識に関する研究

日常生活には，多くの柔軟物体が存在するが，把持や操作を行うごとにその挙動が異なることから，作業をロボットに指示することは困難である．ロボットにより人間のように巧みな柔軟物体の操作が実現すれば，工場等から介護や福祉，家庭環境などに普及していく一助となることが期待される．本研究では，紙を谷折りする作業を対象として，人間によって行われた谷折り操作を認識し，ロボットの作業記述に適した形で記述する手法を提案する．そのために，折り紙作業を逐次的な「操作の連続と見なし」，操作前後の紙の状態と実行された操作の内容を明確にする記述方法を提案し，さらに人間が行う折り操作からその記述に必要なパラメータを推定する手法を提案する．まず，折り紙公理の折り紙の線や点の扱いについて分析し，どのような情報が折り紙公理に基づく作業記述にとって必要か示した．それに基づき折り紙公理で作業を記述するためのデータ構造を定義し，それを用いて折り紙作業を記述する手法を示した．次に，折り線検出に基づく折り操作の認識手法の提案および評価を行った．ここでは，折り操作前後の画像から折り線を画像認識により推定した．その後，行われた操作の種類と折り動作後の折り紙の状態を推定する手法を提案した． 提案した手法に対し実験により評価を行い，この手法により二回折りまでの折り作業が推定可能であることを示した．続いて 上述の手法で対応できない折り方に対応する手法を検討した．この手法では，まず折り動作前の折り紙の状態に対し，折り紙公理から記述可能な全ての折り線を列挙する手法を提案した．その際，折り線には適用された公理の情報を保存することで折り線自体に作業としての情報を持たせた．その後，実際の折り動作後の形状に最も近い折り線を選び出し，折り動作後の折り紙の状態を推定する手法を提案した．示した手法に対して実験を行い，三回折りまでの折り作品に対して，認識可能であることを示した．また，認識失敗した例から，このアルゴリズムが点や線の増加により認識率が低下するが示唆されたため，それに対応するための今後のアルゴリズムの改良についての検討を行った．電気通信大学201

Middleware and Architecture for Advanced Applications of Cyber-physical Systems

In this thesis, we address issues related to middleware, architecture and applications of cyber-physical systems. The first problem we address is the cross-layer design of cyber-physical systems to cope with interactions between the cyber layer and the physical layer in a dynamic environment. We propose a bi-directional middleware that allows the optimal utilization of the common resources for the benefit of either or both the layers in order to obtain overall system performance. The case study of network connectivity preservation in a vehicular formation illustrates how this approach can be applied to a particular situation where the network connectivity drives the application layer. Next we address another aspect of cross-layer impact: the problem that arises when network performance, in this case delay performance, affects control system performance. We propose a two-pronged approach involving a flexible adaptive model identification algorithm with outlier rejection, which in turn uses an adaptive system model to detect and reject outliers, thus shielding the estimation algorithm and thereby improving reliability. We experimentally demonstrate that the outlier rejection approach which intercepts and filters the data, combined with simultaneous model adaptation, can result in improved performance of Model Predictive Control in the vehicular testbed. Then we turn to two advanced applications of cyber-physical systems. First, we address the problem of security of cyber-physical systems. We consider the context of an intelligent transportation system in which a malicious sensor node manipulates the position data of one of the autonomous cars to deviate from a safe trajectory and collide with other cars. In order to secure the safety of such systems where sensor measurements are compromised, we employ the procedure of “dynamic watermarking”. This procedure enables an honest node in the control loop to detect the existence of a malicious node within the feedback loop. We demonstrate in the testbed that dynamic watermarking can indeed protect cars against collisions even in the presence of sensor attacks. The second application of cyber-physical systems that we consider is cyber-manufacturing which is an origami-type laser-based custom manufacturing machine employing folding and cutting of sheet material to manufacture 3D objects. We have developed such a system for use in a laser-based autonomous custom manufacturing machine equipped with real-time sensing and control. The basic elements in the architecture are a laser processing machine, a sensing system to estimate the state of the workpiece, a control system determining control inputs for a laser system based on the estimated data, a robotic arm manipulating the workpiece in the work space, and middleware supporting the communication among the systems. We demonstrate automated 3D laser cutting and bending to fabricate a 3D product as an experimental result. Lastly, we address the problem of traffic management of an unmanned aerial system. In an effort to improve the performance of the traffic management for unmanned aircrafts, we propose a probability-based collision resolution algorithm. The proposed algorithm analyzes the planned trajectories to calculate their collision probabilities, and modifies individual drone starting times to reduce the probability of collision, while attempting to preserve high performance. Our simulation results demonstrate that the proposed algorithm improves the performance of the drone traffic management by guaranteeing high safety with low modification of the starting times

EXTENDING ORIGAMI TECHNIQUE TO FOLD FORMING OF SHEET METAL PRODUCTS

This dissertation presents a scientific based approach for the analysis of folded sheet metal products. Such analysis initializes the examination in terms of topological exploration using set of graph modeling and traversal algorithms. The geometrical validity and optimization are followed by utilizing boundary representation and overlapping detection during a geometrical analysis stage, in this phase the optimization metrics are established to evaluate the unfolded sheet metal design in terms of its manufacturability and cost parameters, such as nesting efficiency, total welding cost, bend lines orientation, and maximum part extent, which aides in handling purposes. The proposed approach evaluates the design in terms of the stressed-based behavior to indicate initial stress performance by utilizing a structural matrix analysis while developing modification factors for the stiffness matrix to cope with the stress-based differences of the diverse flat pattern designs. The outcome from the stressed-based ranking study is mainly the axial stresses as exerted on each element of folded geometry; this knowledge leads to initial optimizing the flat pattern in terms of its stress-based behavior. Furthermore, the sheet folding can also find application in composites manufacturing. Thus, this dissertation optimizes fiber orientation based on the elasticity theory principles, and the best fiber alignment for a flat pattern is determined under certain stresses along with the peel shear on adhesively bonded edges. This study also explores the implementation of the fold forming process within the automotive production lines. This is done using a tool that adopts Quality Function Deployment (QFD) principle and Analytical Hierarchy Process (AHP) methodology to structure the reasoning logic for design decisions. Moreover, the proposed tool accumulates all the knowledge for specific production line and parts design inside an interactive knowledge base. Thus, the system is knowledge-based oriented and exhibits the ability to address design problems as changes occur to the product or the manufacturing process options. Additionally, this technique offers two knowledge bases; the first holds the production requirements and their correlations to essential process attributes, while the second contains available manufacturing processes options and their characteristics to satisfy the needs to fabricate Body in White (BiW) panels. Lastly, the dissertation showcases the developed tools and mathematics using several case studies to verify the developed system\u27s functionality and merits. The results demonstrate the feasibility of the developed methodology in designing sheet metal products via folding

Middleware and Architecture for Advanced Applications of Cyber-physical Systems

In this thesis, we address issues related to middleware, architecture and applications of cyber-physical systems. The first problem we address is the cross-layer design of cyber-physical systems to cope with interactions between the cyber layer and the physical layer in a dynamic environment. We propose a bi-directional middleware that allows the optimal utilization of the common resources for the benefit of either or both the layers in order to obtain overall system performance. The case study of network connectivity preservation in a vehicular formation illustrates how this approach can be applied to a particular situation where the network connectivity drives the application layer. Next we address another aspect of cross-layer impact: the problem that arises when network performance, in this case delay performance, affects control system performance. We propose a two-pronged approach involving a flexible adaptive model identification algorithm with outlier rejection, which in turn uses an adaptive system model to detect and reject outliers, thus shielding the estimation algorithm and thereby improving reliability. We experimentally demonstrate that the outlier rejection approach which intercepts and filters the data, combined with simultaneous model adaptation, can result in improved performance of Model Predictive Control in the vehicular testbed. Then we turn to two advanced applications of cyber-physical systems. First, we address the problem of security of cyber-physical systems. We consider the context of an intelligent transportation system in which a malicious sensor node manipulates the position data of one of the autonomous cars to deviate from a safe trajectory and collide with other cars. In order to secure the safety of such systems where sensor measurements are compromised, we employ the procedure of “dynamic watermarking”. This procedure enables an honest node in the control loop to detect the existence of a malicious node within the feedback loop. We demonstrate in the testbed that dynamic watermarking can indeed protect cars against collisions even in the presence of sensor attacks. The second application of cyber-physical systems that we consider is cyber-manufacturing which is an origami-type laser-based custom manufacturing machine employing folding and cutting of sheet material to manufacture 3D objects. We have developed such a system for use in a laser-based autonomous custom manufacturing machine equipped with real-time sensing and control. The basic elements in the architecture are a laser processing machine, a sensing system to estimate the state of the workpiece, a control system determining control inputs for a laser system based on the estimated data, a robotic arm manipulating the workpiece in the work space, and middleware supporting the communication among the systems. We demonstrate automated 3D laser cutting and bending to fabricate a 3D product as an experimental result. Lastly, we address the problem of traffic management of an unmanned aerial system. In an effort to improve the performance of the traffic management for unmanned aircrafts, we propose a probability-based collision resolution algorithm. The proposed algorithm analyzes the planned trajectories to calculate their collision probabilities, and modifies individual drone starting times to reduce the probability of collision, while attempting to preserve high performance. Our simulation results demonstrate that the proposed algorithm improves the performance of the drone traffic management by guaranteeing high safety with low modification of the starting times

A New Design Method Framework for Open Origami Design Problems

With the development of computer science and manufacturing techniques, modern origami is no longer just used for making artistic shapes as its traditional counterpart was many centuries ago. Instead, the outstanding lightweight and high flexibility of origami structures has expanded their engineering application in aerospace, medical devices, and architecture. In order to support the automatic design of more complex modern origami structures, several computational origami design methods have been established. However these methods still focus on the problem of determining a crease pattern to fold into an exact pre-determined shape. And these methods apply deductive logic and function for only one type of topological origami structure. In order to drop the topological constraints on the shapes, this dissertation introduces the research on the development and implementation of the abductive evolutionary design methods to open origami design problems, which is asking for their designs to achieve geometric and functional requirements instead of an exact shape. This type of open origami design problem has no formal computational solutions yet. Since the open origami design problem requires searching for solutions among arbitrary candidates without fixing to a certain topological formation, it is NP-complete in computational complexity. Therefore, this research selects the genetic algorithm (GA) and one of its variations – the computational evolutionary embryogeny (CEE) – to solve origami problems. The dissertation made two major contributions. One contribution is on creating the GA-based/abstract design method framework on open origami design problems. The other contribution is on the geometric representation of origami designs that directs the definition and mapping of their genetic representation and physical representation. This research introduced two novel geometric representations, which are the “ice-cracking” and the pixelated multicellular representation (PMR). The proposed design methods and the adapted evolutionary operators have been testified by two open origami design problems of making flat-foldable shapes with desired profile area and rigid-foldable 3D water containers with desired volume. The results have proved the proposed methods widely applicable and highly effective in solving the open origami design problems