High accurate absolute robot positioning is a requirement, and still a challenge, in many applications, such as drilling in the aerospace industry. The accuracy is affected due to many sources of errors from robot model, tool calibration, sensor and product uncertainties. While model-based error compensation cannot reach the desired accuracy, sensor-based compensation appears as the practical solution to increase the robot positioning accuracy. A structured analysis of the error sources in robotic manufacturing processes can facilitate error identification and further compensation. This paper describes an error source breaking down approach for analyzing robotic manufacturing processes. Moreover, an external sensor-based compensation is proposed for error reduction and error identification. Comparison with a compliance model-based compensation is performed. The proposed approach is applied to a robotic drilling process for aircraft manufacturing, considered a general and real industrial application. Further validation through experimentation is performed. The validation revealed a clear improvement in robot positioning accuracy and the benefits of the proposed error source structure for analysis
This paper presents a novel concept for wearable support systems based on the approach of the Human Hybrid Robot (HHR), which can be adapted easily to the user and the activity. The concept focuses on modularity and makes intensive use of new manufacturing technologies like 3D-printing as well as flexible kinematics and textile components, in order to fit the system to different individuals and tasks as well as to increase human safety. The main idea can be applied to various applications. In this paper we are focusing on a functional exoskeleton prototype for the upper extremities. It comprises a Human-Machine-Interface (HMI) using a glove equipped with haptic sensors to measure grip force as well as force sensors in a coupling to the user at the forearm. This functional prototype was then successfully evaluated in a blind study with 20 test subjects
Current wearable robots mostly focus on applications in military, rehabilitation and load lifting in the health sector, while they are hardly used in industry and manufacturing. In this paper, a sensor and control concept for a wearable robot for assistance in manual handling of loads in industry is presented. Special requirements such as low costs, direct contact between the human and the load and easy set-up are addressed. A wall-mounted test stand of an actuated elbow joint was built up to evaluate the proposed sensors and control algorithms. By using a torque sensor in the elbow joint as reference it is shown that low cost force sensors in the forearm can be used to measure the human-robot interaction. A torque-based and a velocity-based impedance control approach are compared which allow the user to move freely while not handling any loads and which also allow to incorporate a human command signal for regulation of force support. The former is shown to be superior to the position-based approach. Further, the influence of the human impedance characteristics onto stability of the controllers is discussed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.