Latest Papers

ASME Journal of Mechanisms and Robotics

  • Stable Grasp Control With a Robotic Exoskeleton Glove
    by Vanteddu T, Ben-Tzvi P. on July 28, 2020 at 12:00 am

    AbstractAn exoskeleton robotic glove intended for patients who have suffered paralysis of the hand due to stroke or other factors has been developed and integrated. The robotic glove has the potential to aid patients with grasping objects as part of their daily life activities. Grasp stability was studied and researched by various research groups, but mainly focused on robotic grippers by devising conditions for a stable grasp of objects. Maintaining grasp stability is important so as to reduce the chances of the object slipping and dropping. But there was little focus on the grasp stability of robotic exoskeleton gloves, and most of the research was focused on mechanical design. A robotic exoskeleton glove was developed as well as novel methods to improve the grasp stability. The glove is constructed with rigidly coupled four-bar linkages attached to the finger tips. Each linkage mechanism has one-DOF (degree of freedom) and is actuated by a linear series elastic actuator (SEA). Two methods were developed to satisfy two of the conditions required for a stable grasp. These include deformation prevention of soft objects, and maintaining force and moment equilibrium of the objects being grasped. Simulations were performed to validate the performance of the proposed algorithms. A battery of experiments was performed on the integrated prototype in order to validate the performance of the algorithms developed.

  • Simulation and Analysis of Microspines Interlocking Behavior on Rocky Surfaces: An In-Depth Study of the Isolated Spine
    by Iacoponi S, Calisti M, Laschi C. on July 28, 2020 at 12:00 am

    AbstractMicrospine grippers address a large variety of possible applications, especially in field robotics and manipulation in extreme environments. Predicting and modeling the gripper behavior remains a major challenge to this day. One of the most complex aspects of these predictions is how to model the spine to rock interaction of the spine tip with the local asperity. This paper proposes a single spine model, in order to fill the gap of knowledge in this specific field. A new model for the anchoring resistance of a single spine is proposed and discussed. The model is then applied to a simulation campaign. With the aid of simulations and analytic functions, we correlated performance characteristics of a spine with a set of quantitative, macroscopic variables related to the spine, the substrate and its usage. Eventually, this paper presents some experimental comparison tests and discusses traversal phenomena observed during the tests.

  • Design of an Underactuated Finger Based on a Novel Nine-Bar Mechanism
    by Cheng M, Fan S, Yang D, et al. on July 28, 2020 at 12:00 am

    AbstractElastic elements are commonly adopted to realize underactuation in the design of human-friendly prosthetic hands. The stiffness of these elastic elements, which is a key factor affecting the grasp performance of the underactuated finger, has not well addressed when considering both the stability and adaptability. In this study, an adaptive anthropomorphic finger that adopted a novel nine-bar mechanism is proposed. This nine-bar mechanism is integrated through a coupled four-bar mechanism and an adaptive seven-bar mechanism. The developed finger based on the nine-bar mechanism is able to improve the grasp stability in the global workspace under an extremely small spring stiffness. A quantitative analysis of the grasp stability was carried out. Comparative experiments on the grasps using the finger with/without adaptability were also performed. The results validated that our finger has a good stability when grasping the objects of different sizes.

  • Design of an Accurate and Stiff Wooden Industrial Robot: First Steps Toward Robot Eco-sustainable Mechanical Design
    by Briot S, Kaci L, Boudaud C, et al. on July 28, 2020 at 12:00 am

    AbstractThis article investigates the feasibility of replacing metal robot links by wooden bodies for eco-sustainable design’s purpose. Wood is a material with low environmental impact and a good mass-to-stiffness ratio. However, it has significant dimensional and mechanical variabilities. This is an issue for industrial robots that must be accurate and stiff. To guarantee stiffness and accuracy performance of a wooden robot, we propose an integrated design process combining (i) proper wood selection, (ii) adequate sensor-based control strategies to ensure robot accuracy, and (iii) a robust design approach dealing with wood uncertainties. Based on the use of this integrated design process, a prototype of a wooden five-bar mechanism is designed and manufactured. Experimental results show that it is realistic to design a wooden robot with performance compatible with industry requirements in terms of stiffness (deformations lower than 400 μm for 20 N loads) and accuracy (repeatability lower than 60 μm), guaranteed in a workspace of 800 mm × 200 mm. This study provides a first step toward the eco-sustainable mechanical design of robots.

  • Supernumerary Robotic Limbs to Assist Human Walking With Load Carriage
    by Hao M, Zhang J, Chen K, et al. on July 28, 2020 at 12:00 am

    AbstractWalking with load carriage is a common requirement for individuals in many situations. Legged exoskeletons can transfer the load weight to the ground with rigid-leg structures, thus reducing the load weight borne by the human user. However, the inertia of paralleled structures and the mechanical joint tend to disturb natural motions of human limbs, leading to high-energy consumption. Different from exoskeletons, Supernumerary Robotic Limbs (SuperLimbs) are kinematically independent of the human limbs, thus avoiding the physical interference with the human limbs. In this paper, a SuperLimb system is proposed to assist the human walking with load carriage. The system has two rigid robotic limbs, and each robotic limb has four degrees-of-freedom (DOFs). The SuperLimbs can transfer the load weight to the ground through the rigid structures, thus reducing the weight borne by the human user. A hybrid control strategy is presented to assist the human as well as avoid disturbing user’s natural motions. Motions of the SuperLimb system are generated autonomously to follow the gait of the human user. The gait synchronization is controlled by a finite state machine, which uses inertial sensors to detect the human gait. Human walking experiments are conducted to verify this concept. Experiments indicate that the SuperLimbs can follow the human gait as well as distribute the load weight. Results show that our SuperLimb system can reduce 85.7% of load weight borne by the human when both robotic limbs support and 55.8% load weight on average. This study may inspire the design of other wearable robots and may provide efficient solutions for human loaded walking.

Supernumerary Robotic Limbs to Assist Human Walking With Load Carriage

Abstract

Walking with load carriage is a common requirement for individuals in many situations. Legged exoskeletons can transfer the load weight to the ground with rigid-leg structures, thus reducing the load weight borne by the human user. However, the inertia of paralleled structures and the mechanical joint tend to disturb natural motions of human limbs, leading to high-energy consumption. Different from exoskeletons, Supernumerary Robotic Limbs (SuperLimbs) are kinematically independent of the human limbs, thus avoiding the physical interference with the human limbs. In this paper, a SuperLimb system is proposed to assist the human walking with load carriage. The system has two rigid robotic limbs, and each robotic limb has four degrees-of-freedom (DOFs). The SuperLimbs can transfer the load weight to the ground through the rigid structures, thus reducing the weight borne by the human user. A hybrid control strategy is presented to assist the human as well as avoid disturbing user’s natural motions. Motions of the SuperLimb system are generated autonomously to follow the gait of the human user. The gait synchronization is controlled by a finite state machine, which uses inertial sensors to detect the human gait. Human walking experiments are conducted to verify this concept. Experiments indicate that the SuperLimbs can follow the human gait as well as distribute the load weight. Results show that our SuperLimb system can reduce 85.7% of load weight borne by the human when both robotic limbs support and 55.8% load weight on average. This study may inspire the design of other wearable robots and may provide efficient solutions for human loaded walking.