1,721,038 research outputs found
Improving the Efficiency of Closed-Chain Robotic Systems by the Trajectory Energy Index
Full text linkThis paper deals with the analysis of the impact of the task location within the robot workspace on its energy consumption. The work presents a performance index, which can be used to estimate the most favorable location of a given motion task, regardless of its complexity. The proposed performance index, called Trajectory Energy Index (TEI), is based on the inertial and kinematic properties of the robot, and its computation provides a guideline for defining the minimum-energy position of a task within the robot workspace. The effectiveness in prediction of the TEI is tested for a simple rest-to-rest motion and for a more complex task, which are executed by a two-degree-of-freedom planar robot with closed-loop kinematics
An Interactive Collaborative Robotic System to Play Italian Checkers
Full text linkAn interactive collaborative robotic system to play Italian checkers is presented in this paper. The system detects the state of the game using a camera, calculates the optimal move using a developed decision-making algorithm, and executes pick-and-place tasks to physically move the pieces on the board. The developed system is implemented in a real-world setup using a Franka Emika arm as pieces manipulator. The experimental results show the feasibility of proposed approach
Online optimization of minimum-time and minimum-energy trajectories for a 1-DOF belt-driven robotic system
No full textTrajectory optimization is a critical research area in robotics and automation, especially in manufacturing industries where mechanical systems are often required to minimize the execution time or the consumed energy. In this context, the most common mechanical systems are those with a single degree of freedom because of their simplicity and ease of control. In this paper, we present an approach for the online optimization of minimum-time and minimum-energy trajectories for a robotic system with one degree of freedom. Point-to-point motions of the considered linear axis are planned online, without idle times, by leveraging a verified dynamic model of the robotic system, which also includes an accurate identification of friction parameters. Both minimum-time and minimum-energy trajectories are considered, and the performance of the online optimization using a selected open-source optimization tool is verified in different dynamic conditions of the system. The results of extensive experiments on a belt-driven robotic axis demonstrate the feasibility and the energy-saving capabilities of the proposed approach, as well as the flexibility of the online trajectory optimization in different scenarios, while meeting the kinematics and dynamics limits of the system and guaranteeing low computational time
Nonlinear control of multibody flexible mechanisms: A model-free approach
Full text linkIn this paper a novel nonlinear controller for position and vibration control of flexible-link mechanisms is introduced. The proposed control strategy is model-free and does not require the measurement of the elastic deformation of the mechanism, since the control relies only on the knowledge of the angular position of the actuator and on its time derivative, which can be measured simply with a quadrature encoder. The conditions for the closed-loop stability are evaluated using Lyapunov theory. The performance of the proposed technique is evaluated on a four-bar flexible-link mechanism. Superior vibration damping and more accurate trajectory tracking is obtained in comparison with a PD controller and a fractional order controller, which relies on the same set of measurement as the proposed nonlinear controller
A contact analysis for unconventional mounting processes of angular ball bearings
Full text linkRigorous protocols must be followed when mounting ball bearings to avoid structural damage and subsequent malfunctioning or unexpected failures. Unconventional mounting procedures may produce excessive contact pressures between the elements of the bearing, therefore the whole process must be well-understood and modelled to prevent unwanted effects. Specifically for angular ball bearings, fitting axial forces should always be applied over the raceway subjected to the shrink-fit to avoid contact forces arising on the ball. In the present study, such an axial force is applied unconventionally, such that the axial force is transferred to the shrink-fit raceway through the balls. In this scenario, the evaluation of the contact areas and the pressure distributions is accomplished by exploiting both analytical and FEM approaches, supported by bespoke experimental tests to determine the relevant frictional coefficients and mounting forces. The study demonstrated how analytical methods can successfully replace more demanding FEM-based tools for the evaluation of the bearing mounting force and contact pressure and extent. FEM modelling can, however, be more accurate when dealing with more generic boundary conditions and more intricate geometrical features involved
From the Unimate to the Delta Robot: The Early Decades of Industrial Robotics
Full text linkIn this paper, the early decades of the history of industrial robots (from the 1950’s to the beginning of the 1990’s, approximately) will be described. The history of industrial robotics can be considered starting with Unimate, the first industrial robot designed and built by Devol and Engelberger. The subsequent evolutions of industrial robotics are described in the manuscript, taking into account both the technical and the economic point of view, until the beginning of the 1990’s, when new kinematic structures (parallel robots) appeared, allowing high-speed operations
Path Planning for Special Robotic Operations
Full text linkThe problem of robotic path planning has been the focus of countless investigations since the early works of the ’70s and, despite the large number of results available in literature, is still a topic that draws a great interest. In virtually all robotic applications it is required to somehow define a feasible and safe path, and such a problem can be cast and solved in many ways, given the several possible combination of robots—industrial robots, Autonomous Guided Vehicles (AGVs), Unmanned Aerial Vehicles (UAVs), underwater vehicles—and scenarios—a production line, a warehouse, an hazardous mountain—and therefore a large number of approaches and solutions have been, and are being, investigated. The aim of this chapter is to provide an overview of such widespread literature, first by briefly recalling some classic and general-purpose methods used in path planning, then by focusing on some application-specific problems, related to AGVs in industry, medical robotics and robotic welding. This choice is motivated by the prominent relevance of the path planning problem in these three applications. Then, a single application of great industrial interest, such as robotic spray painting, is analysed. Its specific features are described, and several techniques for task modelling and path planning are considered. A detailed comparison among these techniques is carried out, so as to highlight pros and cons of each one, and to provide a methodology to choose the most suitable one for the specific robotic spray painting application
Playing Checkers with an Intelligent and Collaborative Robotic System †
Full text linkCollaborative robotics represents a modern and efficient framework in which machines can safely interact with humans. Coupled with artificial intelligence (AI) systems, collaborative robots can solve problems that require a certain degree of intelligence not only in industry but also in the entertainment and educational fields. Board games like chess or checkers are a good example. When playing these games, a robotic system has to recognize the board and pieces and estimate their position in the robot reference frame, decide autonomously which is the best move to make (respecting the game rules), and physically execute it. In this paper, an intelligent and collaborative robotic system is presented to play Italian checkers. The system is able to acquire the game state using a camera, select the best move among all the possible ones through a decision-making algorithm, and physically manipulate the game pieces on the board, performing pick-and-place operations. Minimum-time trajectories are optimized online for each pick-and-place operation of the robot so as to make the game more fluent and interactive while meeting the kinematic constraints of the manipulator. The developed system is tested in a real-world setup using a Franka Emika arm with seven degrees of freedom. The experimental results demonstrate the feasibility and performance of the proposed approach
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