双腕アームロボットによる布被覆作業に関する研究

本研究の目的は，物体を布で包む作業（被覆作業）をモデル化し，ロボットによる被覆作業を実現させることである．本論文では「目標線」の概念に基づいて物体を布で包む作業（被覆作業）をモデル化することを提案した．これにより，まず人間が大まかな包み方を教示し，次に布と物体の形状から被覆作業を計画し，最終的にロボットの動作を生成し，ロボットによる被覆作業を実現した．近年，工場のロボット化が行われているが，ロボット化できない作業はまだまだ存在している．それらは，人間にしか行えないような巧みで複雑な作業，あるいは，ロボットより人間の方が効率的にできてしまうような作業である．そのような作業の１つとして，布を扱う作業が挙げられる．布を扱う作業の中には，布単体だけでなく，物体も一緒に取り扱っていく被覆作業が多く存在している．しかし，この被覆作業をロボットに指示するための有効な作業モデルは確立されていない．先行研究では，ロボットによる布操作の記述方法として，点，折り線や手先経路が用いられている．また，コンピュータグラフィクス分野では目標線という記述方法があり，これは被覆を表現するために用いられている．被覆作業をロボット化する上では，まず，実世界のロボットのために，汎用的な被覆モデルとして必要となる物体と布の関係や作業手順を，どのように記述すればいいのかという問題に直面する．このような点を考慮し，被覆作業に適した記述モデルを導入しなければならない．次に，そのような被覆のための作業記述を，実際のロボットにどのように入力すればいいのかという問題がある．煩雑な指示方法ではなく，実空間上で人間が考えている被覆作業を，直感的にロボットに指示できるのが望ましい．最後に，その作業記述から実際のロボットの動きをどのように生成すればよいのかという問題が現れてくる．ロボットが被覆作業を達成するためには，実際の手先軌道や干渉を回避するための動作を，状況に合わせて生成しなければならない．以上を踏まえて，本研究ではロボットによる被覆作業の課題に取り組んだ．具体的には以下の課題について取り組んだ．・布と物体の関係を適切に表す記述方法・直感的な被覆手順の指示方法・ロボットの動作軌道の生成方法まず，布と物体の関係を適切に表す記述方法について検討した．本研究では，コンピュータグラフィクス分野で用いられた目標線という記述方法を，実空間のロボットに導入することを提案した．この目標線は平面だけでなく曲面形状への指示が行いやすい．そして，物体のどこを布で包んでいくかという被覆の本質的な情報を自然に表せる利点を持つ．その中では，凹凸が存在するような物体に対しても被覆を行う場合があり，その凹凸を適切に処理して，作業を記述する必要がある．そこで，物体の埋めるべき凹部と埋めるべきでない凹部分を考慮し，凹凸へ適切な目標線指示を行うための局所凸という概念，及び局所凸生成方法を提案した．次に，直感的な被覆手順の指示方法について検討した．本研究では，人間の大まかな包む指示と被覆の関係を考え，物体と布のどこを重ね合わせるかという人間の被覆の意図を目標線として入力する方法を提案した．本研究は，作業指示を行う手の正確な３次元的な軌跡ではなく，手の軌跡とその軌跡が通過していく物体表面の関係に注目した．そして，デプスセンサとモーションキャプチャセンサを組合せた教示デバイスを用いて，人間の被覆の意図を抽出した．その中では，指示中の手振れの影響を小さくするための目標線逆走防止処理手法とスムージングと間引き処理を合わせた補正処理手法を提案した．最後に，ロボットの動作軌道の生成方法について検討した．本研究では，目標線と把持点から布の動きを表す手先経路を生成する方法と，その手先経路を実行するためのロボット動作の生成方法を提案した．実際のロボットを動かすためには，目標線だけでなく，手先経路や動作指令が必要であり，可動域や物体との干渉を考慮し，右手と左手を用いた布の持ち替えや持ち直しを行わなければならない．これらの情報を生成する上で，目標線が被覆の本質的な情報を保持している．そのため，手先経路・動作指令は自動的に生成可能である．動作生成手法の中では，各操作の布への重力の影響，動作ステップ数やロボットと布の位置関係を考慮した確実性を求め，それを基に生成された動作遷移グラフを用いて，最適な持ち替えや持ち直し操作の組み合わせを計画する方法を提案した．以上，本研究では，物体を布で包むという被覆作業について，ロボット化のための枠組みを提案した．さらに，各課題に対する提案方法を統合し，一連の被覆作業システムとして実装した．これにより，実際に人間の大まかな指示から，目標線を用いて布と物体の関係を記述し，そこから布の動きを表す手先経路，状況に合わせた最適なロボット動作を生成できるようになりロボットによる被覆作業が実現した．電気通信大学201

Learning to Rearrange Deformable Cables, Fabrics, and Bags with Goal-Conditioned Transporter Networks

Rearranging and manipulating deformable objects such as cables, fabrics, and bags is a long-standing challenge in robotic manipulation. The complex dynamics and high-dimensional configuration spaces of deformables, compared to rigid objects, make manipulation difficult not only for multi-step planning, but even for goal specification. Goals cannot be as easily specified as rigid object poses, and may involve complex relative spatial relations such as "place the item inside the bag". In this work, we develop a suite of simulated benchmarks with 1D, 2D, and 3D deformable structures, including tasks that involve image-based goal-conditioning and multi-step deformable manipulation. We propose embedding goal-conditioning into Transporter Networks, a recently proposed model architecture for learning robotic manipulation that rearranges deep features to infer displacements that can represent pick and place actions. We demonstrate that goal-conditioned Transporter Networks enable agents to manipulate deformable structures into flexibly specified configurations without test-time visual anchors for target locations. We also significantly extend prior results using Transporter Networks for manipulating deformable objects by testing on tasks with 2D and 3D deformables. Supplementary material is available at https://berkeleyautomation.github.io/bags/.Comment: See https://berkeleyautomation.github.io/bags/ for project website and code; v2 corrects some BibTeX entries, v3 is ICRA 2021 version (minor revisions

Data-driven robotic manipulation of cloth-like deformable objects : the present, challenges and future prospects

Manipulating cloth-like deformable objects (CDOs) is a long-standing problem in the robotics community. CDOs are flexible (non-rigid) objects that do not show a detectable level of compression strength while two points on the article are pushed towards each other and include objects such as ropes (1D), fabrics (2D) and bags (3D). In general, CDOs’ many degrees of freedom (DoF) introduce severe self-occlusion and complex state–action dynamics as significant obstacles to perception and manipulation systems. These challenges exacerbate existing issues of modern robotic control methods such as imitation learning (IL) and reinforcement learning (RL). This review focuses on the application details of data-driven control methods on four major task families in this domain: cloth shaping, knot tying/untying, dressing and bag manipulation. Furthermore, we identify specific inductive biases in these four domains that present challenges for more general IL and RL algorithms.Publisher PDFPeer reviewe

The development of a process for the production of textiles with fully embedded electronics

Many attempts to combine Electronics and Textiles have been realised for many years now. At the beginning with the introduction of conductive wires, then with the introduction of sensors and more complex circuits onto an everyday garment. The next step of evolution of combining these seemingly different fields is to integrate the electronics inside a textile structure, so that it will provide a seamless implementation of both worlds into everyday life. The microelectronics, mechanical, electrical, computing and chemical engineering advances of the last years, can ensure that, nowadays, this is feasible. Because of the minuscule dimensions of the electronic components, so that can be integrated inside the thin-by-nature yarn, and the necessity of a flexible and bendable structure overall, the task required is not of a small scale and has no prerequisite. This Thesis provides the backbone of an innovative technique to achieve the above goal in an automated or semi-automated, accurate, repeatable, reliable and time-cost effective way, combining all the required procedures, outlining the issues and proposing solutions on a plethora of them. This research's outcome, after both manual and automated implementation of the microelectronic component encapsulation concept, proves that automation of the process is feasible with more research and funding in the future. Because this is an innovative and challenging in its implementation, as far as the tiny dimensions of the electronic components are concerned, more testing and physical implementation must be conducted with the contribution of a team of people from different disciplines, in order to finalise it and produce the first linear and continuous version of the machine that can automatically produce electronic yarns, i.e. yarn with electronic components inside its core. The importance of this Thesis is that it sets the foundations, guidelines and requirements for the development of an all-new manufacturing procedure and the creation of a new machine, i.e. the Electronic Yarn Machine -EYM- in the future

Study and development of sensorimotor interfaces for robotic human augmentation

This thesis presents my research contribution to robotics and haptics in the context of human augmentation. In particular, in this document, we are interested in bodily or sensorimotor augmentation, thus the augmentation of humans by supernumerary robotic limbs (SRL). The field of sensorimotor augmentation is new in robotics and thanks to the combination with neuroscience, great leaps forward have already been made in the past 10 years. All of the research work I produced during my Ph.D. focused on the development and study of fundamental technology for human augmentation by robotics: the sensorimotor interface. This new concept is born to indicate a wearable device which has two main purposes, the first is to extract the input generated by the movement of the user's body, and the second to provide the somatosensory system of the user with an haptic feedback. This thesis starts with an exploratory study of integration between robotic and haptic devices, intending to combine state-of-the-art devices. This allowed us to realize that we still need to understand how to improve the interface that will allow us to feel the agency when using an augmentative robot. At this point, the path of this thesis forks into two alternative ways that have been adopted to improve the interaction between the human and the robot. In this regard, the first path we presented tackles two aspects conerning the haptic feedback of sensorimotor interfaces, which are the choice of the positioning and the effectiveness of the discrete haptic feedback. In the second way we attempted to lighten a supernumerary finger, focusing on the agility of use and the lightness of the device. One of the main findings of this thesis is that haptic feedback is considered to be helpful by stroke patients, but this does not mitigate the fact that the cumbersomeness of the devices is a deterrent to their use. Preliminary results here presented show that both the path we chose to improve sensorimotor augmentation worked: the presence of the haptic feedback improves the performance of sensorimotor interfaces, the co-positioning of haptic feedback and the input taken from the human body can improve the effectiveness of these interfaces, and creating a lightweight version of a SRL is a viable solution for recovering the grasping function

HERO Glove

Non-repetitive manipulation tasks that are easy for humans to perform are difficult for autonomous robots to execute. The Haptic Exoskeletal Robot Operator (HERO) Glove is a system designed for users to remotely control robot manipulators whilst providing sensory feedback to the user. This realistic haptic feedback is achieved through the use of toroidal air-filled actuators that stiffen up around the user’s fingers. Tactile sensor data is sent from the robot to the HERO Glove, where it is used to vary the pressure in the toroidal actuators to simulate the sense of touch. Curvature sensors and inertial measurement units are used to capture the glove’s pose to control the robot

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

Aerial-aquatic robots capable of crossing the air-water boundary and hitchhiking on surfaces.

Many real-world applications for robots-such as long-term aerial and underwater observation, cross-medium operations, and marine life surveys-require robots with the ability to move between the air-water boundary. Here, we describe an aerial-aquatic hitchhiking robot that is self-contained for flying, swimming, and attaching to surfaces in both air and water and that can seamlessly move between the two. We describe this robot's redundant, hydrostatically enhanced hitchhiking device, inspired by the morphology of a remora (Echeneis naucrates) disc, which works in both air and water. As with the biological remora disc, this device has separate lamellar compartments for redundant sealing, which enables the robot to achieve adhesion and hitchhike with only partial disc attachment. The self-contained, rotor-based aerial-aquatic robot, which has passively morphing propellers that unfold in the air and fold underwater, can cross the air-water boundary in 0.35 second. The robot can perform rapid attachment and detachment on challenging surfaces both in air and under water, including curved, rough, incomplete, and biofouling surfaces, and achieve long-duration adhesion with minimal oscillation. We also show that the robot can attach to and hitchhike on moving surfaces. In field tests, we show that the robot can record video in both media and move objects across the air/water boundary in a mountain stream and the ocean. We envision that this study can pave the way for future robots with autonomous biological detection, monitoring, and tracking capabilities in a wide variety of aerial-aquatic environments

Automated lay-up of composite blades

"Automated Lay-Up of Composite Blades" describes the Author’s contribution to a joint research project between Dowty Aerospace Propellers and the University of Durham into the automated lay-up of complex, three dimensional carbon fibre composite propfan blade preforms. The emphasis of the highly applied Project, now continuing at Brunei University, has been to develop an operational research demonstrator cell. The existing manual lay-up techniques employed by Dowty have been reviewed and a new met ho logy devised which can be far more easily automated. To implement the new met ho logy, a specialized lay-up station has been developed along with a practical prototype vacuum gripper technology capable of manipulating the range of large, complex, flexible and easily distorted plies required for propfan preform manufacture. Both the gripper technology and the Lay-Up Station have been successfully tested, the latter in an industrial environment to manufacture "real life” propfan blades