1,720,972 research outputs found
Practical range of applicability of a linear stiffness model of an elliptical flexure hinge
No full textThis paper presents the analysis of a linear stiffness model of an elliptical flexure hinge. The purpose of the study is to support the mechanical designer in choosing the geometric dimensions of the hinge based on design specifications, driven by the accuracy that can later be achieved in planning its motion using the related stiffness model. Results are presented as a comparison between the analytical model and a finite element model of the flexure hinge, showing the practical range of applicability of the analytical model and its limitations. A case study show how to design a flexure hinge of small size for micro scale robotic or mechatronic operations
Collaborative Robotics for Rehabilitation: A Multibody Model for Kinematic and Dynamic Analysis
No full textHuman-Robot Collaboration is increasing in industrial settings because of the robot’s accuracy and repeatability join perfectly with human’s problem solving to enhance the industrial productivity. Collaborative robots share the workspace with operators in order to reduce human workload and guarantee performances. The reliability and safety of these robots allow their application in the health care sector (e.g. neuromuscular rehabilitation). The cobot-assisted therapy is becoming a significant supplement to the traditional one aimed at providing intensive and repetitive rehabilitating tasks to improve the patient’s recovery. The human-robot system presented in this paper is a closed kinematic chain composed of a robotic arm attached to the human forearm through a custom handle system. The handle, designed with simple components, is used for primary rehabilitation exercises. The kinematic models of human and robotic arms presented in this study are applied to develop trajectory planning algorithm in the joint space. Robot joints torques needed for guiding the patient limb are obtained by multibody dynamic simulations, assessing the capability of the manipulator to perform the task at given speeds and loads. The tools and methods proposed in this work allow for a preliminary study on cobot-assisted-therapy by different human-cobot-working modalities
A Framework for the Study of Human-Robot Collaboration in Rehabilitation Practices
No full textCollaborative robots and humans can cooperate in different industrial processes by combining their peculiar skills: the accuracy and repeatability of the manipulators can be exploited in synergy with human intelligence and flexibility. Since the cobots are safe and reliable, they can be adopted in the health sector, in particular in rehabilitation: the cobots allow the three-dimensional manipulation of the limbs and can be easily adapted to different anthropometric parameters. The kinematic models of the human-robot system presented in this paper can be exploited to develop motion planning algorithms for rehabilitation exercises. Furthermore, the estimation of the interaction forces in the human-robot interface can be obtained by multibody dynamic simulations. The proposed methodology is a starting point for the study of the integration of cobots into current rehabilitation practices, evaluating the feasibility and providing useful ideas in order to plan different man-robot working modalities
From Dataset Creation to Defect Detection: A Proposed Procedure for a Custom CNN Approach for Polishing Applications on Low-Performance PCs
Full text linkThis study focuses on training a custom, small Convolutional Neural Network (CNN) using a limited dataset through data augmentation that is aimed at developing weights for subsequent fine-tuning on specific defects, namely improperly polished aluminum surfaces. The objective is to adapt the network for use in computationally restricted environments. The methodology involves using two computers—a low-performance PC for network creation and initial testing and a more powerful PC for network training using the Darknet framework—after which the network is transferred back to the initial low-performance PC. The results demonstrate that the custom lightweight network suited for a low-performance PC effectively performs object detection under the described conditions. These findings suggest that using tailored lightweight networks for recognizing specific types of defects is feasible and warrants further investigation to enhance the industrial defect detection processes in limited computational settings. This approach highlights the potential for deploying AI-driven quality control in environments with constrained hardware capabilities
Modelling and control of a spherical robotic device
No full textThe researchers at the Polytechnic University of Marche developed a spherical parallel manipulator designed for the orientation of parts or tools: the paper presents the first experimental results on such innovative machine. A model of the prototype robot has been realised by means of commercial multibody software then both open-loop and closed loop dynamics has been studied. The relative simplicity of machine kinematics allowed also to experiment the use of controllers with compensation of gravitational terms
A collision avoidance strategy for redundant manipulators in dynamically variable environments: On-line perturbations of off-line generated trajectories
No full textIn this work, a comprehensive control strategy for obstacle avoidance in redundant manipulation is presented, consisting of a combination of off-line path planning algorithms with on-line motion control. Path planning allows the avoidance of fixed obstacles detected before the start of the robot’s motion; it is based on the potential fields method combined with a smoothing process realized by means of interpolation with Bezier curves. The on-line motion control is designed to compensate for the motion of the obstacles and to avoid collisions along the kinematic chain of the manipulator; it is realized by means of a velocity control law based on the null space method for redundancy control. A new term is introduced in the control law to take into account the speed of the obstacles as well as their position. Simulations on a simplified planar case are presented to assess the validity of the algorithms and to estimate the computational effort in order to verify the transferability of our approach to a real system
Real-Time Strategy for Obstacle Avoidance in Redundant Manipulators
No full textA robot working in a space shared with humans and obstacles needs an obstacle avoidance strategy. In this work, a kinematic control algorithm of a redundant robotic system for real-time obstacle avoidance is presented. The workspace is populated by fixed and moving obstacles. To plan a trajectory in real time, an artificial potential field and a distance algorithm are introduced: an artificial force set, composed by an attractive force towards the goal and repulsive forces from the obstacles, drives the robot end-effector in the workspace; at the same time repulsive velocities act on control points along the links of the robot, avoiding contacts with obstacles all over the serial kinematic chain of the manipulator. The algorithm has been implemented in a 2D environment for a 3R planar manipulator in order to assess the algorithm and present preliminary results. The strategy presented in this study will be the starting point for a more complex problem in 3D space with a 7-DOF redundant manipulator
A Comparative Analysis on a Limited Image Dataset for Accurately Detecting Improperly Polished Surfaces for Industrial Applications
Full text linkThe objective of this study is to identify the optimal object detection architecture for training on a specific type of defect detection, namely incorrectly polished surfaces on aluminium elements. In order to facilitate a meaningful comparison of the various architectures, a maximum training time of approximately one hour was established for each architecture. Using the Darknet framework and a specific dataset, five architectures were compared (for the time being). The parameters of the various architectures, including network size, number of batches, and so forth, were modified according to a well-defined and systematic procedure. The preliminary findings indicate that the YOLOv4-tiny network exhibits superior training performance on this dataset, rendering it an optimal choice for industrial applications. This research provides support to small and medium-sized enterprises (SMEs) by identifying effective object detection architectures for quality control and highlighting avenues for advancing AI-driven defect detection in manufacturing
A Proposal for a Simplified Systematic Procedure for the Selection of Electric Motors for Land Vehicles with an Emphasis on Fuel Economy
Full text linkThe selection of the electric motor for the propulsion system in electric vehicles is a crucial step, as it determines the final performance of the vehicle. The design of the propulsion system of an electric vehicle, although similar in principle to that of a conventional endothermic engine, requires a change in vision. Indeed, the main problem in an electric vehicle is its range, which depends not only on the weight of the vehicle but also on the type of powertrain, type of transmission and engine, several factors that are difficult to assess at an early stage. In some cases, during the preliminary design phase of the propulsion system, one simply estimates the maximum power required by the vehicle, neglecting the calculation of the range. This evaluation is postponed to later stages, causing increased complexity and interaction during the propulsion system evaluation process. In this study, vehicle autonomy is taken into account from the outset with the aim to reduce this iteration. This paper proposes a preliminary electric motor selection method for land vehicles, highlighting the importance of smoothing the sampled data of driving cycles. A method for obtaining approximate efficiency maps of the electric motor is also illustrated, and it is shown how the total gear ratio affects vehicle energy consumption. Ultimately, this work makes a contribution to the design of more efficient and high-performance electric vehicles. This topic is more oriented to helping automotive manufactures choose in a fast and structured way electric motors for their vehicles
A Flexible Framework for Robotic Post-Processing of 3D Printed Components
No full textThree-dimensional (3D) printing has revolutionized the production of mechanical components by enabling the creation of objects of complex geometry, but at the same time it has introduced new issues related to post-processing operations. Similarly, robotics has seen an evolution with the emergence of collaborative robots, which can support the operator in human-centric applications. This work aims to bring these two technologies together by presenting a flexible framework for processing raw products obtained through 3D printing technology with the support of collaborative robotics. This framework lays the foundation for the subsequent development of a human-robot cooperation protocol with the aim of simplifying post-processing and particularly finishing operations of metal-printed 3D objects. In this paper, an initial integrated solution is proposed that can address the post-processing needs of objects from 3D printing, providing guidance on the software and hardware tools to be used and the process to be followed to achieve a quality product in compliance with the relevant standards. Verifications in a simulation environment and through algorithms based on the kinematics and statics of a Fanuc collaborative robot implemented in a numerical environment allow verification of the feasibility of several operations. The result is a comprehensive framework that starts from the feasibility study and reaches the completion of the 3D printed component through finishing and post-processing operations
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