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Title: high-precise robot arm manipulation based on online iterative learning and forward simulation with positioning error below end-effector physical minimum displacement.

Abstract: Precision is a crucial performance indicator for robot arms, as high precision manipulation allows for a wider range of applications. Traditional methods for improving robot arm precision rely on error compensation. However, these methods are often not robust and lack adaptability. Learning-based methods offer greater flexibility and adaptability, while current researches show that they often fall short in achieving high precision and struggle to handle many scenarios requiring high precision. In this paper, we propose a novel high-precision robot arm manipulation framework based on online iterative learning and forward simulation, which can achieve positioning error (precision) less than end-effector physical minimum displacement. Additionally, we parallelize multiple high-precision manipulation strategies to better combine online iterative learning and forward simulation. Furthermore, we consider the joint angular resolution of the real robot arm, which is usually neglected in related works. A series of experiments on both simulation and real UR3 robot arm platforms demonstrate that our proposed method is effective and promising. The related code will be available soon.

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Design and implementation of Arduino based robotic arm

<p><span>This study presents the model, design, and construction of the Arduino based robotic arm, which functions across a distance as it is controlled through a mobile application. A six degree of freedom robotic arm has been designed and implemented for the purpose of this research. The design controlled by the Arduino platform receives orders from the user’s mobile application through wireless controlling signals, that is Bluetooth. The arm is made up of five rotary joints and an end effector, where rotary motion is provided by the servomotor. Each link has been first designed using solid works and then printed by 3D printer. The assembly of the parts of the robot and the motor’s mechanical shapes produce the final prototype of the arm. The Arduino has been programmed to provide rotation to each corresponding servo motor to the sliders in the designed mobile application for usage from distance.</span></p>

A simple linear driving actuator for robotic arm used in land-deep sea

Inverse kinematics for a 7-dof humanoid robotic arm with joint limit and end pose coupling, revision total knee arthroplasty using robotic arm technology, building of inmoov robotic arm for performing various operations.

Abstract: ‘Automation is the key in reducing the repetitive and banal tasks of everyday life’, the oft-quoted aphorism best portrays our effort at making a humanoid hand for tasks that require dexterity of fingers in situations where time and effort are of importance. The cost of human labor, quality of processes or products, time, and safety make this project a need of the hour. The research paper showcases our efforts of making a humanoid robotic arm. The body of the arm is composed of 3D printed parts. Servo Motors with nylon strings were used to control the fingers and the wrist. InMoov Nervo Board was used to control the servos. Worm Gear Mechanism was implemented to control the bicep movement and Worm Wheel is used for shoulder rotation. Machines can perform a wide range of functions without a considerable amount of human intervention. The future scope of Robotics and Automation would be to make a diverse and positive impact in industrial as well as research applications. Keywords: 3D Print, Build Challenges, Electronics, Humanoid, Inmoov, MyRobotLab, Robotic Arm, Robotics

An integrated system design interface for operating 8-DoF robotic arm

This study examines the system integration of a game engine with robotics middleware to drive an 8 degree offreedom (DoF) robotic upper limb to generate human-like motion for telerobotic applications. The developed architectureencompasses a pipeline execution design using Blender Game Engine (BGE) including the acquisition of real humanmovements via the Microsoft Kinect V2, interfaced with a modeled virtual arm, and replication of similar arm movements on the physical robotic arm. In particular, this study emphasizes the integration of a human “pilot” with ways to drive such a robotic arm through simulation and later, into a finished system. Additionally, using motion capture technology, a human upper limb action was recorded and applied onto the robot arm using the proposed architecture flow. Also, we showcase the robotic arm’s actions which include reaching, picking, holding, and dropping an object. This paper presentsa simple and intuitive kinematic modeling and 3D simulation process, which is validated using 8-DoF articulated robot to demonstrate methods for animation, and simulation using the designed interface.

Estimation of the Energy Consumption of an All-Terrain Mobile Manipulator for Operations in Steep Vineyards

A heterogeneous robotic system that can perform various tasks in the steep vineyards of the Mediterranean region was developed and tested as part of the HEKTOR—Heterogeneous Autonomous Robotic System in Viticulture and Mariculture—project. This article describes the design of hardware and an easy-to-use method for evaluating the energy consumption of the system, as well as, indirectly, its deployment readiness level. The heterogeneous robotic system itself consisted of a flying robot—a light autonomous aerial robot (LAAR)—and a ground robot—an all-terrain mobile manipulator (ATMM), composed of an all-terrain mobile robot (ATMR) platform and a seven-degree-of-freedom (DoF) torque-controlled robotic arm. A formal approach to describe the topology and parameters of selected vineyards is presented. It is shown how Google Earth data can be used to make an initial estimation of energy consumption for a selected vineyard. On this basis, estimates of energy consumption were made for the tasks of protective spraying and bud rubbing. The experiments were conducted in two different vineyards, one with a moderate slope and the other with a much steeper slope, to evaluate the proposed estimation method.

Does One Size Fit All? A Case Study to Discuss Findings of an Augmented Hands-Free Robot Teleoperation Concept for People with and without Motor Disabilities

Hands-free robot teleoperation and augmented reality have the potential to create an inclusive environment for people with motor disabilities. It may allow them to teleoperate robotic arms to manipulate objects. However, the experiences evoked by the same teleoperation concept and augmented reality can vary significantly for people with motor disabilities compared to those without disabilities. In this paper, we report the experiences of Miss L., a person with multiple sclerosis, when teleoperating a robotic arm in a hands-free multimodal manner using a virtual menu and visual hints presented through the Microsoft HoloLens 2. We discuss our findings and compare her experiences to those of people without disabilities using the same teleoperation concept. Additionally, we present three learning points from comparing these experiences: a re-evaluation of the metrics used to measure performance, being aware of the bias, and considering variability in abilities, which evokes different experiences. We consider these learning points can be extrapolated to carrying human–robot interaction evaluations with mixed groups of participants with and without disabilities.

Robotic-arm assisted unicompartmental knee arthroplasty system has a learning curve of 11 cases and increased operating time

Algebraic models based on trigonometric and cramer's rules for computing inverse kinematics of robotic arm, export citation format, share document.

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