Article
Automation & Control Systems
Federico Barravecchia, Mirco Bartolomei, Luca Mastrogiacomo, Fiorenzo Franceschini
Summary: The advent of collaborative robotics has enabled humans and robots to closely collaborate in manufacturing activities, leveraging their unique strengths and capabilities. The partnership between humans and robots, often described as symbiotic, encompasses a wide range of interactions, some beneficial and others detrimental. This study aims to understand the principles of Human-Robot Symbiosis and proposes a new approach for evaluating assembly tasks based on the characteristics of symbiotic relationships.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2023)
Article
Automation & Control Systems
Andrea Casalino, Andrea Maria Zanchettin, Luigi Piroddi, Paolo Rocco
Summary: This article introduces a scheduling method for collaborative assembly tasks that optimally plans assembly activities and reduces idle time to improve manufacturing efficiency.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2021)
Article
Robotics
Valentin N. Hartmann, Andreas Orthey, Danny Driess, Ozgur S. Oguz, Marc Toussaint
Summary: Robotic construction assembly planning is a parallelizable task and motion planning problem. We propose a planning system that parallelizes complex task and motion planning by solving smaller subproblems. By combining optimization methods and a sampling-based path planner, we can plan cooperative multi-robot manipulation with unknown arrival times. We demonstrate the robustness and scalability of this approach in multiple construction case studies and showcase the feasibility of executing the computed plans in the real world.
IEEE TRANSACTIONS ON ROBOTICS
(2023)
Article
Computer Science, Interdisciplinary Applications
S. Mutti, G. Nicola, M. Beschi, N. Pedrocchi, L. Molinari Tosatti
Summary: Optimizing work-piece position in multi-robot cells in industry often relies on heuristics, which can be time-consuming. This study proposes an iterative layered-optimization method that integrates Whale Optimization and Ant Colony Optimization algorithms to achieve optimized solutions along a working path.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Computer Science, Artificial Intelligence
Giovanni Boschetti, Matteo Bottin, Maurizio Faccio, Riccardo Minto
Summary: This article introduces the development trend of collaborative assembly systems, the establishment of simulation environments, and the conceptualization and application of related mathematical models. The results show that the performance of the system is influenced by various factors, and a relatively accurate method for evaluating the system performance is proposed.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Construction & Building Technology
Ahmed Khairadeen Ali, One Jae Lee, Hayub Song
Summary: The study proposes an optimization process using static performance criteria in the design stage of construction project to automatically search for the best picking location within the reach of the robot arm, aiming to solve limitations in robotic construction implementation and increase productivity.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
Veniamin Tereshchuk, Nikolay Bykov, Samuel Pedigo, Santosh Devasia, Ashis G. Banerjee
Summary: This study proposes a two-step data-driven approach to automatically select task precedence relations and generate policies to improve efficiency in multi-robot task allocation. Experimental results demonstrate that the method outperforms a baseline partition-based scheduler by approximately 17%-19%, and the learned policies can select better scheduling heuristics without additional computational costs.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Engineering, Manufacturing
Mohammad Safeea, Richard Bearee, Pedro Neto
Summary: Additive manufacturing is revolutionizing industry by allowing rapid and affordable prototyping and fabrication of custom-made parts. This study proposes a novel multitasking collaborative robot-assisted additive manufacturing framework, which demonstrates the feasibility of the system through experimental tests.
JOURNAL OF MANUFACTURING PROCESSES
(2022)
Article
Computer Science, Artificial Intelligence
Jian Yang, Yuhui Shi
Summary: With the increasing complexity of tasks and uncertainty in the environment, achieving adaptability and robustness for multi-robot cooperation tasks through manual design methods is challenging. Automatic synthesis approaches with trial and error mechanisms are gaining more attention. The proposed Brain Storm Robotics (BSR) framework encodes strategies as "ideas" and can obtain satisfactory solutions for specific tasks through a series of operations on these ideas. This paper proposes an automatic design approach for neural network-based strategies using the BSR framework to achieve cooperative behaviors in robotic swarms.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Niccolo Lucci, Andrea Monguzzi, Andrea Maria Zanchettin, Paolo Rocco
Summary: With the emergence of Industry 4.0, industries are required to offer customized products with numerous tailored features, which cannot be provided by a traditional robotic assembly line. This paper introduces a general library of atomic Predicates combined with first-order logic, allowing for the modeling of general industrial assembly processes in human-robot collaboration. These Predicates are mainly utilized to recognize human activities, enabling the modeling and supervision of workflows.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Computer Science, Interdisciplinary Applications
Li Zhang, Yizhe Liu, Huidong Bai, Qianyuan Zou, Zhuang Chang, Weiping He, Shuxia Wang, Mark Billinghurst
Summary: This study proposes a robot-enabled tangible interface that provides physical feedback for virtual assembly in virtual reality. The system improves system usability and sense of presence by dynamically moving a physical structure with a robotic arm. The user evaluation results show that the system increases task completion time but significantly enhances the haptic experience and system usability.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Robotics
Tommaso Proietti, Ciaran O'Neill, Cameron J. Hohimer, Kristin Nuckols, Megan E. Clarke, Yu Meng Zhou, David J. Lin, Conor J. Walsh
Summary: This study presents a textile-based multi-joint soft wearable robot for assisting upper limb movements, incorporating dynamic Gravity Compensation and Joint Trajectory Tracking controllers. The robot showed effectiveness in providing assistance and mechanical transparency when powered off, allowing users to perform daily activities without restrictions.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Engineering, Manufacturing
Sichao Liu, Lihui Wang, Xi Vincent Wang
Summary: This article investigates multimodal data-driven robot control for human-robot collaborative assembly. A programming-free human-robot interface is designed to fuse multimodal human commands, and deep learning is explored for accurate translation of brainwave command phrases into robot commands. Event-driven function blocks are used for high-level robot control, and a case study is conducted to demonstrate the effectiveness of the system.
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
(2022)
Article
Robotics
Daojing Lin, Niandong Jiao, Zhidong Wang, Lianqing Liu
Summary: Magnetic field-controlled continuum robots can be steered dexterously within a small space, a novel magnetic continuum robot with multi-mode control has been proposed and studied, showing improved dexterity and workspace compared to other uniform-magnetized robots.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Robotics
Janine Hoelscher, Mengyu Fu, Inbar Fried, Maxwell Emerson, Tayfun Efe Ertop, Margaret Rox, Alan Kuntz, Jason A. Akulian, Robert J. Webster, Ron Alterovitz
Summary: The study introduces a new sampling-based planning method for a steerable needle lung robot, which has the capability to accurately reach targets in most regions of the lung. The new strategy allows faster performance, reaching targets more efficiently and arriving at lower-risk paths in a shorter time compared to existing techniques.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
