Design, fabrication and control of soft robots

Conventionally, engineers have employed rigid materials to fabricate precise, predictable robotic systems, which are easily modelled as rigid members connected at discrete joints. Natural systems, however, often match or exceed the performance of robotic systems with deformable bodies. Cephalopods, for example, achieve amazing feats of manipulation and locomotion without a skeleton; even vertebrates such as humans achieve dynamic gaits by storing elastic energy in their compliant bones and soft tissues. Inspired by nature, engineers have begun to explore the design and control of soft-bodied robots composed of compliant materials. This Review discusses recent developments in the emerging field of soft robotics.National Science Foundation (U.S.) (Grant IIS-1226883

Deep Learning of Force Manifolds from the Simulated Physics of Robotic Paper Folding

Robotic manipulation of slender objects is challenging, especially when the induced deformations are large and nonlinear. Traditionally, learning-based control approaches, such as imitation learning, have been used to address deformable material manipulation. These approaches lack generality and often suffer critical failure from a simple switch of material, geometric, and/or environmental (e.g., friction) properties. This article tackles a fundamental but difficult deformable manipulation task: forming a predefined fold in paper with only a single manipulator. A data-driven framework combining physically-accurate simulation and machine learning is used to train a deep neural network capable of predicting the external forces induced on the manipulated paper given a grasp position. We frame the problem using scaling analysis, resulting in a control framework robust against material and geometric changes. Path planning is then carried out over the generated "neural force manifold" to produce robot manipulation trajectories optimized to prevent sliding, with offline trajectory generation finishing 15$\times$ faster than previous physics-based folding methods. The inference speed of the trained model enables the incorporation of real-time visual feedback to achieve closed-loop sensorimotor control. Real-world experiments demonstrate that our framework can greatly improve robotic manipulation performance compared to state-of-the-art folding strategies, even when manipulating paper objects of various materials and shapes.Comment: Supplementary video is available on YouTube: https://youtu.be/k0nexYGy-P

Stability of control system in handling of a flexible object by rigid arm robots

科研費報告書収録論文(課題番号:07455416・基盤研究(B)(2)・H7～H9/研究代表者:内山, 勝/フレキシブル双腕ロボットの協調制御に関する研究

Multi-Segment Parallel Continuum Manipulator

Continuum manipulators are a type of robot arm that resemble biological tentacles and trunks. They have a flexible and compliant structure, which may allow them to out-perform rigid-link designs in cluttered workspaces or in environments that contain people. While most continuum manipulators are required to have constant curvature along the length of each segment, a new design known as a parallel continuum manipulator removes this restriction and inherits some properties of parallel rigid-link robots such as greater stability, precision, strength, and maneuverability. Until now, only single segment forms of these manipulators have been created. This project expands this manipulator design concept by creating the first multi-segment parallel continuum manipulator

The Development of a Sensitive Manipulation End Effector

This thesis designed and realized a two-degree of freedom wrist and two finger manipulator that completes the six-degree of freedom Sensitive Manipulation Platform, the arm of which was previously developed. This platform extends the previous research in the field of robotics by covering not only the end effector with deformable tactile sensors, but also the links of the arm. Having tactile sensors on the arm will improve the dynamic model of the system during contact with its environment and will allow research in contact navigation to be explored. This type of research is intended for developing algorithms for exploring dynamic environments. Unlike traditional robots that focus on collision avoidance, this platform is designed to seek out contact and use it to gather important information about its surroundings. This small desktop platform was designed to have similar proportions and properties to a small human arm. These properties include compliant joints and tactile sensitivity along the lengths of the arms. The primary applications for the completed platform will be research in contact navigation and manipulation in dynamic environments. However, there are countless potential applications for a compliant arm with increased tactile feedback, including prosthetics and domestic robotics. This thesis covers the details behind the design, analysis, and evaluation of the two degrees of the Wrist and two two-link fingers, with particular attention being given to the integration of series elastics actuators, the decoupling of the fingers from the wrist, and the incorporation of tactile sensors in both the forearm motor module and fingers

Benchmarking Cerebellar Control

Cerebellar models have long been advocated as viable models for robot dynamics control. Building on an increasing insight in and knowledge of the biological cerebellum, many models have been greatly refined, of which some computational models have emerged with useful properties with respect to robot dynamics control. Looking at the application side, however, there is a totally different picture. Not only is there not one robot on the market which uses anything remotely connected with cerebellar control, but even in research labs most testbeds for cerebellar models are restricted to toy problems. Such applications hardly ever exceed the complexity of a 2 DoF simulated robot arm; a task which is hardly representative for the field of robotics, or relates to realistic applications. In order to bring the amalgamation of the two fields forwards, we advocate the use of a set of robotics benchmarks, on which existing and new computational cerebellar models can be comparatively tested. It is clear that the traditional approach to solve robotics dynamics loses ground with the advancing complexity of robotic structures; there is a desire for adaptive methods which can compete as traditional control methods do for traditional robots. In this paper we try to lay down the successes and problems in the fields of cerebellar modelling as well as robot dynamics control. By analyzing the common ground, a set of benchmarks is suggested which may serve as typical robot applications for cerebellar models

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world