A variable stiffness soft gripper using granular jamming and biologically inspired pneumatic muscles

As the domains in which robots operate change the objects a robot may be required to grasp and manipulate are likely to vary significantly and often. Furthermore there is increasing likelihood that in the future robots will work collaboratively alongside people. There has therefore been interest in the development of biologically inspired robot designs which take inspiration from nature. This paper presents the design and testing of a variable stiffness, three fingered soft gripper which uses pneumatic muscles to actuate the fingers and granular jamming to vary their stiffness. This gripper is able to adjust its stiffness depending upon how fragile/deformable the object being grasped is. It is also lightweight and low inertia making it better suited to operation near people. Each finger is formed from a cylindrical rubber bladder filled with a granular material. It is shown how decreasing the pressure inside the finger increases the jamming effect and raises finger stiffness. The paper shows experimentally how the finger stiffness can be increased from 21 to 71 N/m. The paper also describes the kinematics of the fingers and demonstrates how they can be position-controlled at a range of different stiffness values

Study on Control Methodology of Compliant Manipulation Utilizing Additional Contact with Environment

制度:新 ; 報告番号:甲3297号 ; 学位の種類:博士(工学) ; 授与年月日:2011/2/25 ; 早大学位記番号:新560

Design of a variable stiffness soft dexterous gripper

This article presents the design of a variable stiffness, soft, three fingered dexterous gripper. The gripper uses two designs of McKibben muscles. Extensor muscles which increase in length when pressurised are used to form the fingers of the gripper. Contractor muscles which decrease in length when pressurised are then used to apply forces to the fingers via tendons which cause flexion and extension of the fingers. The two types of muscles are arranged to act antagonistically and this means that by raising the pressure in all of the pneumatic muscles the stiffness of the system can be increased without a resulting change in finger position. The article presents the design of the gripper, some basic kinematics to describe its function and then experimental results demonstrating the ability to adjust the bending stiffness of the gripper’s fingers. It has been demonstrated that the finger’s bending stiffness can be increased by over 150%. The article concludes by demonstrating that the fingers can be closed loop position controlled and are able to track step and sinusoidal inputs

Active compliance control strategies for multifingered robot hand

Safety issues have to be enhanced when the robot hand is grasping objects of different shapes, sizes and stiffness. The inability to control the grasping force and finger stiffness can lead to unsafe grasping environment. Although many researches have been conducted to resolve the grasping issues, particularly for the object with different shape, size and stiffness, the grasping control still requires further improvement. Hence, the primary aim of this work is to assess and improve the safety of the robot hand. One of the methods that allows a safe grasping is by employing an active compliance control via the force and impedance control. The implementation of force control considers the proportional–integral–derivative (PID) controller. Meanwhile, the implementation of impedance control employs the integral slidingmode controller (ISMC) and adaptive controller. A series of experiments and simulations is used to demonstrate the fundamental principles of robot grasping. Objects with different shape, size and stiffness are tested using a 3-Finger Adaptive Robot Gripper. The work introduces the Modbus remote terminal unit [RTU] protocol, a low-cost force sensor and the Arduino IO Package for a real-time hardware setup. It is found that, the results of the force control via PID controller are feasible to maintain the grasped object at certain positions, depending on the desired grasping force (i.e., 1N and 8N). Meanwhile, the implementation of impedance control via ISMC and adaptive controller yields multiple stiffness levels for the robot fingers and able to reduce collision between the fingers and the object. However, it was found that the adaptive controller produces better impedance control results as compared to the ISMC, with a 33% efficiency improvement. This work lays important foundations for long-term related research, particularly in the field of active compliance control that can be beneficial to human–robot interaction (HRI)

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

An anthropomorphic soft skeleton hand exploiting conditional models for piano playing.

The development of robotic manipulators and hands that show dexterity, adaptability, and subtle behavior comparable to human hands is an unsolved research challenge. In this article, we considered the passive dynamics of mechanically complex systems, such as a skeleton hand, as an approach to improving adaptability, dexterity, and richness of behavioral diversity of such robotic manipulators. With the use of state-of-the-art multimaterial three-dimensional printing technologies, it is possible to design and construct complex passive structures, namely, a complex anthropomorphic skeleton hand that shows anisotropic mechanical stiffness. We introduce a concept, termed the "conditional model," that exploits the anisotropic stiffness of complex soft-rigid hybrid systems. In this approach, the physical configuration, environment conditions, and conditional actuation (applied actuation) resulted in an observable conditional model, allowing joint actuation through passivity-based dynamic interactions. The conditional model approach allowed the physical configuration and actuation to be altered, enabling a single skeleton hand to perform three different phrases of piano music with varying styles and forms and facilitating improved dynamic behaviors and interactions with the piano over those achievable with a rigid end effector

Constrained motion planning and execution for soft robots

There are many reasons why a compliant robot is expected to perform better than a rigid one in interaction tasks, which include limitation of interaction forces, resilience to modeling errors, robustness, naturalness of motion, and energy efficiency. Most of these reasons are apparent if one thinks of how the human body interacts with its environment. However, most of the work in robotic planning and control of interaction has been traditionally developed for rigid robot models. Indeed, planning and control for compliant robots can be substantially harder. In this thesis, I propose the point of view that the difficulties encountered in planning and control for soft robots are at least in part due to the fact that the same approaches previously used for rigid robots are used as a starting point and adapted. On the opposite, if new methods are considered that start from consideration of compliance from the very beginning, the planning and control problems can be of comparable difficulty, or even substantially simpler, than their rigid counterpart. I will argue this thesis with two main examples. The first part of this thesis presents a new approach to integrate motion planning and control for robots in interaction. One of the peculiarities of interaction tasks is that the robot limbs and the environment form "closed kinematic chains". If rigid models are considered, the dynamics of robots in interaction become constrained, and Differential Algebraic Equations replace Ordinary Differential Equations, i.e. typically a much harder problem to deal with. However, in the thesis I show that this is not necessarily so. Indeed, consideration of compliance allows to have a more tractable mathematical model of interacting systems, and to introduce more sophisticated control approaches. Specifically, we present a novel geometric control scheme under which for constrained robot systems we achieve decoupled interaction control (i.e. make position errors irrelevant to force control, and viceversa). Based on this result, it is possible to decouple the planning problem in two separate aspects. On one side, we make dealing with motion planning of the constrained system easier by relaxing the geometric constraint, i.e. replacing the lower--dimensional constraint manifold with a narrow but full-dimensional boundary layer. This allows us to plan motion using state-of-the-art methods, such as RRT*, on points within the boundary layer, which we can efficiently sample. On the other side we control interaction forces, i.e. forces generated by displacements in the perpendicular direction to the tangent space of the constraint manifold. Thanks to the (locally) noninteracting control characteristic of our scheme, the two controllers can be applied separately and in sequence, so that the interaction force controller can correct for any discrepancies resulting from the boundary layer approximation used in the constrained position controller. The geometric noninteracting controller can be applied both in simulation for planning, and in real time for execution control. Moreover, while it does rely on considering a model of compliance in the system, it does not make any assumption on the amount of compliance in the system - or in other words, it applies equally well to stiff but elastic robots. The final outcome of the two-stage planner is an effective (possibly optimal from RRT*) trajectory that satisfies constraint with arbitrarily good approximation, asymptotically rejecting perturbations coming from sampled displacements. The second part of this thesis is dedicated to study grasp planning for hands that are simple -- in the sense of low number of actuated degrees of freedom -- but soft, i.e. continuously deformable in an infinity of possible shapes through interaction with objects. Once again, the use of such "soft hands" brings about a change of paradigm in grasp planning with respect to classical rigid multi-dof grasp planning, which only apparently makes the problem harder. However, in this thesis I show that thanks to the correct combination of compliance and underactuation of soft hands, together with the set of all possible physical interactions between the hand, the object and the environment, the grasping problem can be redefined. The new definition includes the possible combination of hand-object functional interactions which I address as "Enabling Constraints". The use of Enabling Constraints constitutes a rather new challenge for existing grasping algorithms: adaptation to totally or partially unknown scenes remains a difficult task, toward which only some approaches have been investigated so far. In this thesis I present a first approach to the study of this novel kind of manipulation. It is based on an accurate simulation tool and starts from the considerations that hand compliance can be used to adapt to the shape of the surrounding objects and that rather than considering the environment as and obstacle to avoid, it can be used in turn to functionally shape the hand. I show that thanks to this functionality the problem of generating grasping postures for soft hands can be reduced to grasp basic geometries (e.g. cylinders or boxes) in which the geometry of the object can be decomposed