Differential Spiral Joint Mechanism for Coupled Variable Stiffness Actuation

In this study, we present the Differential Spiral Joint (DSJ) mechanism for variable stiffness actuation in tendon-driven robots. The DSJ mechanism semi-decouples the modulation of position and mechanical stiffness, allowing independent trajectory tracking in different parameter space. Past studies show that increasing the mechanical stiffness achieves the wider range of renderable stiffness, whereas decreasing the mechanical stiffness improves the quality of actuator decoupling and shock absorbance. Therefore, it is often useful to modulate the mechanical stiffness to balance the required level of stiffness and safety. In addition, the DSJ mechanism offers a compact form factor, which is suitable for applications where the size and weight are important. The performance of the DSJ mechanism in various areas is validated through a set of experiments

Design and analysis of a variable-stiffness robotic gripper

This paper presents the design and analysis of a novel variable-stiffness robotic gripper, the RobInLab VS gripper. The purpose is to have a gripper that is strong and reliable as rigid grippers but adaptable as soft grippers. This is achieved by designing modular fingers that combine a jamming material core with an external structure, made with rigid and flexible materials. This allows the finger to softly adapt to object shapes when the capsule is not active, but becomes rigid when air suction is applied. A three-finger gripper prototype was built using this approach. Its validity and performance are evaluated using five experimental benchmark tests implemented exclusively to measure variable-stiffness grippers. To complete the analysis, our gripper is compared with an alternative gripper built by following a relevant state-of-the-art design. Our results suggest that our solution significantly outperforms previous approaches using similar variable stiffness designs, with a significantly higher grasping force, combining a good shape adaptability with a simpler and more robust design.This paper describes research conducted at UJI Robotic Intelligence Laboratory. Support for this laboratory is provided in part by Ministerio de Ciencia e Innnovación (DPI2015-69041-R and DPI2017-89910-R), by Universitat Jaume I (UJI-B2018-74), and by Generalitat Valenciana (PROMETEO/2020/034)

Control strategies for cleaning robots in domestic applications: A comprehensive review:

Service robots are built and developed for various applications to support humans as companion, caretaker, or domestic support. As the number of elderly people grows, service robots will be in increasing demand. Particularly, one of the main tasks performed by elderly people, and others, is the complex task of cleaning. Therefore, cleaning tasks, such as sweeping floors, washing dishes, and wiping windows, have been developed for the domestic environment using service robots or robot manipulators with several control approaches. This article is primarily focused on control methodology used for cleaning tasks. Specifically, this work mainly discusses classical control and learning-based controlled methods. The classical control approaches, which consist of position control, force control, and impedance control , are commonly used for cleaning purposes in a highly controlled environment. However, classical control methods cannot be generalized for cluttered environment so that learning-based control methods could be an alternative solution. Learning-based control methods for cleaning tasks can encompass three approaches: learning from demonstration (LfD), supervised learning (SL), and reinforcement learning (RL). These control approaches have their own capabilities to generalize the cleaning tasks in the new environment. For example, LfD, which many research groups have used for cleaning tasks, can generate complex cleaning trajectories based on human demonstration. Also, SL can support the prediction of dirt areas and cleaning motion using large number of data set. Finally, RL can learn cleaning actions and interact with the new environment by the robot itself. In this context, this article aims to provide a general overview of robotic cleaning tasks based on different types of control methods using manipulator. It also suggest a description of the future directions of cleaning tasks based on the evaluation of the control approaches

Soft Robot-Assisted Minimally Invasive Surgery and Interventions: Advances and Outlook

Since the emergence of soft robotics around two decades ago, research interest in the field has escalated at a pace. It is fuelled by the industry's appreciation of the wide range of soft materials available that can be used to create highly dexterous robots with adaptability characteristics far beyond that which can be achieved with rigid component devices. The ability, inherent in soft robots, to compliantly adapt to the environment, has significantly sparked interest from the surgical robotics community. This article provides an in-depth overview of recent progress and outlines the remaining challenges in the development of soft robotics for minimally invasive surgery

Model Based Control of Soft Robots: A Survey of the State of the Art and Open Challenges

Continuum soft robots are mechanical systems entirely made of continuously deformable elements. This design solution aims to bring robots closer to invertebrate animals and soft appendices of vertebrate animals (e.g., an elephant's trunk, a monkey's tail). This work aims to introduce the control theorist perspective to this novel development in robotics. We aim to remove the barriers to entry into this field by presenting existing results and future challenges using a unified language and within a coherent framework. Indeed, the main difficulty in entering this field is the wide variability of terminology and scientific backgrounds, making it quite hard to acquire a comprehensive view on the topic. Another limiting factor is that it is not obvious where to draw a clear line between the limitations imposed by the technology not being mature yet and the challenges intrinsic to this class of robots. In this work, we argue that the intrinsic effects are the continuum or multi-body dynamics, the presence of a non-negligible elastic potential field, and the variability in sensing and actuation strategies.Comment: 69 pages, 13 figure

Quantifying the Evolutionary Self Structuring of Embodied Cognitive Networks

We outline a possible theoretical framework for the quantitative modeling of networked embodied cognitive systems. We notice that: 1) information self structuring through sensory-motor coordination does not deterministically occur in Rn vector space, a generic multivariable space, but in SE(3), the group structure of the possible motions of a body in space; 2) it happens in a stochastic open ended environment. These observations may simplify, at the price of a certain abstraction, the modeling and the design of self organization processes based on the maximization of some informational measures, such as mutual information. Furthermore, by providing closed form or computationally lighter algorithms, it may significantly reduce the computational burden of their implementation. We propose a modeling framework which aims to give new tools for the design of networks of new artificial self organizing, embodied and intelligent agents and the reverse engineering of natural ones. At this point, it represents much a theoretical conjecture and it has still to be experimentally verified whether this model will be useful in practice.

On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas

Elongation Modeling and Compensation for the Flexible Tendon-Sheath System

In tendon-driven systems, the elongation of the tendon would result in inaccuracy in the position control of the system. This becomes a critical challenge for those applications, such as surgical robots, which require the tendon-sheath system with flexible and even time-varying configurations but lack of corresponding sensory feedback at the distal end due to spatial restrictions. In this paper, we endeavor to address this problem by modeling the tendon elongation in a flexible tendon-sheath system. Targeting at flexibility in practical scenarios, we first derived a model describing the relationship between the overall tendon elongation and the input tension with arbitrary route configurations. It is shown that changes in the route configuration would significantly affect the tendon elongation. We also proposed a remedy to enhance the system tolerance against potential unmodeled perturbations along the transmission route during operation. A scaling factor S was introduced as a design guideline to determine the scaling effect. A dedicated platform that was able to measure the tensions at both ends and the overall tendon elongation was designed and set up to validate the new findings. Discussions were made on the performance and the future implementation of the proposed models and remedy.published_or_final_versio