Learning Tool Morphology for Contact-Rich Manipulation Tasks with Differentiable Simulation

When humans perform contact-rich manipulation tasks, customized tools are often necessary and play an important role in simplifying the task. For instance, in our daily life, we use various utensils for handling food, such as knives, forks and spoons. Similarly, customized tools for robots may enable them to more easily perform a variety of tasks. Here, we present an end-to-end framework to automatically learn tool morphology for contact-rich manipulation tasks by leveraging differentiable physics simulators. Previous work approached this problem by introducing manually constructed priors that required detailed specification of object 3D model, grasp pose and task description to facilitate the search or optimization. In our approach, we instead only need to define the objective with respect to the task performance and enable learning a robust morphology by randomizing the task variations. The optimization is made tractable by casting this as a continual learning problem. We demonstrate the effectiveness of our method for designing new tools in several scenarios such as winding ropes, flipping a box and pushing peas onto a scoop in simulation. We also validate that the shapes discovered by our method help real robots succeed in these scenarios

Dynamic Modeling, Design and Control of Wire-Borne Underactuated Brachiating Robots: Theory and Application

The ability of mobile robots to locomote safely in unstructured environments will be a cornerstone of robotics of the future. Introducing robots into fully unstructured environments is known to be a notoriously difficult problem in the robotics field. As a result, many of today's mobile robots are confined to prepared level surfaces in laboratory settings or relatively controlled environments only. One avenue for deploying mobile robots into unstructured settings is to utilize elevated wire networks. The research conducted under this thesis lays the groundwork for developing a new class of wire-borne underactuated robots that employs brachiation -- swinging like an ape -- as a means of locomotion on flexible cables. Executing safe brachiation maneuvers with a cable-suspended underactuated robot is a challenging problem due to the complications induced by the cable dynamics and vibrations. This thesis studies, from concept through experiments, the dynamic modeling techniques and control algorithms for wire-borne underactuated brachiating robots, to develop advanced locomotion strategies that enable the robots to perform energy-efficient and robust brachiation motions on flexible cables. High-fidelity and approximate dynamic models are derived for the robot-cable system, which provide the ability to model the interactions between the cable and the robot and to include the flexible cable dynamics in the control design. An optimal trajectory generation framework is presented in which the flexible cable dynamics are explicitly accounted for when designing the optimal swing trajectories. By employing a variety of control-theoretic methods such as robust and adaptive estimation, control Lyapunov and barrier functions, semidefinite programming and sum-of-squares optimization, a set of closed-loop control algorithms are proposed. A novel hardware brachiating robot design and embodiment are presented, which incorporate unique mechanical design features and provide a reliable testbed for experimental validation of the wire-borne underactuated brachiating robots. Extensive simulation results and hardware experiments demonstrate that the proposed multi-body dynamic models, trajectory optimization frameworks, and feedback control algorithms prove highly useful in real world settings and achieve reliable brachiation performance in the presence of uncertainties, disturbances, actuator limits and safety constraints.Ph.D

Trajectory Generation and Control for Quadrotors

This thesis presents contributions to the state-of-the-art in quadrotor control, payload transportation with single and multiple quadrotors, and trajectory generation for single and multiple quadrotors. In Ch. 2 we describe a controller capable of handling large roll and pitch angles that enables a quadrotor to follow trajectories requiring large accelerations and also recover from extreme initial conditions. In Ch. 3 we describe a method that allows teams of quadrotors to work together to carry payloads that they could not carry individually. In Ch. 4 we discuss an online parameter estimation method for quadrotors transporting payloads which enables a quadrotor to use its dynamics in order to learn about the payload it is carrying and also adapt its control law in order to improve tracking performance. In Ch. 5 we present a trajectory generation method that enables quadrotors to fly through narrow gaps at various orientations and perch on inclined surfaces. Chapter 6 discusses a method for generating dynamically optimal trajectories through a series of predefined waypoints and safe corridors and Ch. 7 extends that method to enable heterogeneous quadrotor teams to quickly rearrange formations and avoid a small number of obstacles

RoboCook: Long-Horizon Elasto-Plastic Object Manipulation with Diverse Tools

Humans excel in complex long-horizon soft body manipulation tasks via flexible tool use: bread baking requires a knife to slice the dough and a rolling pin to flatten it. Often regarded as a hallmark of human cognition, tool use in autonomous robots remains limited due to challenges in understanding tool-object interactions. Here we develop an intelligent robotic system, RoboCook, which perceives, models, and manipulates elasto-plastic objects with various tools. RoboCook uses point cloud scene representations, models tool-object interactions with Graph Neural Networks (GNNs), and combines tool classification with self-supervised policy learning to devise manipulation plans. We demonstrate that from just 20 minutes of real-world interaction data per tool, a general-purpose robot arm can learn complex long-horizon soft object manipulation tasks, such as making dumplings and alphabet letter cookies. Extensive evaluations show that RoboCook substantially outperforms state-of-the-art approaches, exhibits robustness against severe external disturbances, and demonstrates adaptability to different materials.Comment: Project page: https://hshi74.github.io/robocook

Stochastic Approach for Modeling a Soft Robotic Finger with Creep Behavior

Soft robots have high adaptability and safeness which are derived from their softness, and therefore it is paid attention to use them in human society. However, the controllability of soft robots is not enough to perform dexterous behaviors when considering soft robots as alternative laborers for humans. The model-based control is effective to achieve dexterous behaviors. When considering building a model which is suitable for control, there are problems based on their special properties such as the creep behavior or the variability of motion. In this paper, the lumped parameterized model with viscoelastic joints for a soft finger is established for the creep behavior. Parameters are expressed as distributions, which makes it possible to take into account the variability of motion. Furthermore, stochastic analyses are performed based on the parameters' distribution. They show high adaptivity compared with experimental results and also enable the investigation of the effects of parameters for robots' variability.Comment: 17 pages, 8 figures. This is a preprint of an article submitted for consideration in Advanced Robotics, copyright Taylor & Francis and Robotics Society of Japan; Advanced Robotics is available online at http://www.tandfonline.com

Forward Kinematics Based Prediction for Bending Motion of Soft Pneumatic Actuators with Various Air Chambers

This study proposes a forward kinematic model for soft actuators that utilize pneumatic control to predict their bending motion, which is simulated using Ansys software. Firstly, a bending motion test is conducted with a 2-air chamber actuator to derive an equation that establishes the relationship between the bending angle and input pressure. Next, a serial model for the overall soft actuator is developed using forward kinematics with the DH method. The angle variables in the soft actuator are then replaced with an equation that relates the deformed angle and compressed air. Finally, the proposed serial model is used to predict the bending motion of 4-air and 6-air chamber actuators, and the results are compared to simulations and real experiments. The comparison shows that the proposed model could accurately predict the bending motion of the real actuators within an acceptable tolerance of 10%

A shape memory alloy-based biomimetic robotic hand : design, modelling and experimental evaluation

Every year more the 400,000 people are subject to an upper limb amputation. Projections foresee that this number may double by the 2050. Infections, trauma, cancer, or complications that arise in blood vessels represent the main causes for amputations. The access to prosthetic care is worldwide extremely limited. This is mainly due to the high cost both of commercially available prostheses and of the rehabilitation procedure which every prostheses user has to endure. Aside from high costs, commercially available hand prostheses have faced high rejection rates, mainly due to the their heavy weight, noisy operation and also to the unnatural feel of the fingers. To overcome these limitations, new materials, such as Shape Memory Alloys (SMAs), have been considered as potential candidate actuators for these kind of devices. In order to provide a contribution in the development of performant and easily affordable hand prostheses, the development of a novel and cost-effective five-fingered hand prototype actuated by Shape Memory Alloy (SMA) wires is presented in this work. The dissertation starts with the description of a first generation of a SMA actuated finger. Structure assemblage and performances in term of force, motion and reactiveness are investigated to highlight advantages and disadvantages of the prototype. In order to improve the achievable performances, a second generation of SMA actuated finger having soft features is introduced. Its structure, a five-fingered hand prosthesis having intrinsically elastic fingers, capable to grasp several types of objects with a considerable force, and an entirely 3D printed structure is then presented. Comparing this prototype with the most important prostheses developed so far, relevant advantages especially in term of noiseless actuation, cost, weight, responsiveness and force can be highlighted. A finite element based framework is then developed, to enable additional structure optimization and further improve the SMA finger performances. On the same time, a concentrated parameters physics-based model is formulated to allow, in the future, an easier control of the device, characterized by strong nonlinearities mainly due to the Shape Memory alloy hysteretic behavior.Jedes Jahr werden weltweit bei mehr als 400.000 Menschen Amputationen der oberen Gliedmaßen durchgeführt. Prognosen gehen davon aus, dass sich diese Zahl bis zum Jahr 2050 verdoppeln wird. Hauptursachen der Amputationen sind Infektionen, Unfälle, Krebs oder Durchblutungsstörungen. Der Zugang zu prothetischer Versorgung ist besonders in den Entwicklungsländern stark eingeschränkt. Dies liegt vor allem an den hohen Kosten sowohl der im Handel erhältlichen Prothesen als auch des Rehabilitationsprozesses, den jeder Prothesenträger durchlaufen muss. Neben den hohen Kosten haben kommerziell erhältliche Handprothesen aufgrund ihres hohen Gewichts, des lauten Betriebes und auch des unnatürlichen Gefühls hohe Ablehnungsraten. Um diese Einschränkungen zu überwinden, wurden neue Materialien, wie z.B. Formgedächtnislegierungen (SMAs), als potenzielle Materialien für den Antrieb von Prothesen untersucht . Um einen Beitrag zur Entwicklung von leistungsfähigen und erschwinglichen Handprothesen zu leisten, wird in dieser Arbeit die Entwicklung eines neuartigen und kostengünstigen Fünf-Finger-Handprototyps vorgestellt, der durch Drähte aus Formgedächtnislegierungen aktiviert wird. Die Doktorarbeit beginnt mit der Beschreibung der ersten Generation eines SMA-aktivierten Fingers. Zuerst wird der Aufbau und das Wirkungsprinzip des SMA Fingers erläutert und die Leistungs- und Bewegungsfähigkeit des Systems untersucht sowie Vor- und Nachteile des Prototyps dargestellt. Anschließend, um die erreichbare Leistungsfähigkeit zu verbessern, wird eine zweite Generation von SMA-gesteuerten Fingern vorgestellt, die eine vollständig in 3D gedruckte Struktur aufweisen. Diese Fünffinger-Handprothese mit inhärent elastischen Fingern ermöglicht nicht nur das Greifen unterschiedlich geformter Objekte sondern auch das Heben und Halten schwerer Gegenstände. Dieser neuartige Prototyp wird mit den wichtigsten bisher entwickelten Prothesen verglichen und die relevanten Vorteile insbesondere in Bezug auf geräuschlose Ansteuerung, Kosten, Gewicht, Reaktionszeit und Kraft hervorgehoben. Abschließend wird ein Finite-Elemente-Modell entwickelt, mit Hilfe dessen die Fingerstruktur weiter optimiert und die Leistungsfähigkeit des SMA-Fingers noch verbessert werden kann. Zusätzlich wird ein Konzentriertes-Parameter-Modell formuliert, um, in der Zukunft, eine leichtere Regelung des Systems zu ermöglichen. Dieses ist notwendig, da der SMA-Finger starke Nichtlinearitäten aufweist, die auf das hysteretische Verhalten der Formgedächtnislegierung zurückzuführen sind

Scalable Tactile Sensing for an Omni-adaptive Soft Robot Finger

Robotic fingers made of soft material and compliant structures usually lead to superior adaptation when interacting with the unstructured physical environment. In this paper, we present an embedded sensing solution using optical fibers for an omni-adaptive soft robotic finger with exceptional adaptation in all directions. In particular, we managed to insert a pair of optical fibers inside the finger's structural cavity without interfering with its adaptive performance. The resultant integration is scalable as a versatile, low-cost, and moisture-proof solution for physically safe human-robot interaction. In addition, we experimented with our finger design for an object sorting task and identified sectional diameters of 94\% objects within the $\pm$6mm error and measured 80\% of the structural strains within $\pm$0.1mm/mm error. The proposed sensor design opens many doors in future applications of soft robotics for scalable and adaptive physical interactions in the unstructured environment.Comment: 8 pages, 6 figures, full-length version of a submission to IEEE RoboSoft 202