Metamorphic parallel mechanisms (MPMs) are a class of mechanisms that possess adaptability and reconfigurability to change permanent finite mobility based on topological structure change. Metamorphic parallel mechanisms keep the advantages of traditional parallel mechanisms in terms of high load-carrying capacity, good positioning accuracy and low inertia but with reconfiguration. MPMs are a new class of reconfigurable parallel mechanisms and have not been studied much. Therefore, this thesis is devoted to explore the fundamentals of mechanism theory on MPMs by focusing on two parts: (1) Systematic Methods of Synthesizing and Designing Metamorphic Parallel Mechanisms: A general strategy using reconfigurable joint to construct reconfigurable limbs has been proposed on synthesizing metamorphic parallel mechanisms and a general synthesis procedure has been provided based on screw theory. With two invented reconfigurable joints, many metamorphic parallel mechanisms have been obtained using the proposed method and their reconfiguration has been modelled in terms of geometric constraints. From the design point of view, the design parameters need to serve all phases of a metamorphic parallel mechanism. Thus a unified design performance representation is desired. Based on this, motion/force transmissibility is proposed to unifying the performance representation for optimal design of metamorphic parallel mechanisms considering all working phases and performance in each phase. Optimal design examples are demonstrated on some selected metamorphic parallel mechanisms. (2) Unified Kinematics and Dynamics Modelling of Metamorphic Parallel Mechanisms: Since each of all reconfigured phases of a metamorphic parallel mechanism is equivalent to a traditional parallel mechanism and all phases with different mobility share the same mechanical structure, a unified strategy has been proposed by considering the reconfiguration of the joint and taking the reconfigured phases as special cases of the general configuration. Some selected metamorphic parallel mechanisms have been studied and their unified kinematics, workspace representation, and dynamics modelling are solved. Thus this thesis provides basic synthesis, design, and modelling theory for metamorphic parallel mechanisms considering their reconfiguration and variable mobility.
Barsotti, Annalisa, Khalaf, Kinda, and Gan, Dongming
2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) Engineering in Medicine & Biology Society (EMBC), 2020 42nd Annual International Conference of the IEEE. :3138-3141 Jul, 2020
Robotic vision plays a key role for perceiving the environment in grasping applications. However, the conventional framed-based robotic vision, suffering from motion blur and low sampling rate, may not meet the automation needs of evolving industrial requirements. This paper, for the first time, proposes an event-based robotic grasping framework for multiple known and unknown objects in a cluttered scene. Compared with standard frame-based vision, neuromorphic vision has advantages of microsecond-level sampling rate and no motion blur. Building on that, the model-based and model-free approaches are developed for known and unknown objects' grasping respectively. For the model-based approach, event-based multi-view approach is used to localize the objects in the scene, and then point cloud processing allows for the clustering and registering of objects. Differently, the proposed model-free approach utilizes the developed event-based object segmentation, visual servoing and grasp planning to localize, align to, and grasp the targeting object. The proposed approaches are experimentally validated with objects of different sizes, using a UR10 robot with an eye-in-hand neuromorphic camera and a Barrett hand gripper. Moreover, the robustness of the two proposed event-based grasping approaches are validated in a low-light environment. This low-light operating ability shows a great advantage over the grasping using the standard frame-based vision. Furthermore, the developed model-free approach demonstrates the advantage of dealing with unknown object without prior knowledge compared to the proposed model-based approach. Comment: 37 pages
2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Intelligent Robots and Systems (IROS), 2019 IEEE/RSJ International Conference on. :3328-3334 Nov, 2019
Muthusamy, Rajkumar, Indave, Jose Miguel, Muthusamy, Praveen Kumar, Hasan, Eman Fayez, Zweiri, Yahya, Kyrki, Ville, and Gan, Dongming
2019 IEEE 9th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER) CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), 2019 IEEE 9th Annual International Conference on. :889-895 Jul, 2019
Albalasie, Ahmad, Hussain, Irfan, Horoub, Mamon, Khan, Sikandar, Ali, Sajid, and Gan, Dongming
2019 IEEE 9th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems (CYBER) CYBER Technology in Automation, Control, and Intelligent Systems (CYBER), 2019 IEEE 9th Annual International Conference on. :70-75 Jul, 2019
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Intelligent Robots and Systems (IROS), 2018 IEEE/RSJ International Conference on. :7047-7054 Oct, 2018
2018 International Conference on Reconfigurable Mechanisms and Robots (ReMAR) Reconfigurable Mechanisms and Robots (ReMAR), 2018 International Conference on. :1-9 Jun, 2018
Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition, and I.2, I.2.9, I.2.10, I.2.1
Abstract
Slip detection is essential for robots to make robust grasping and fine manipulation. In this paper, a novel dynamic vision-based finger system for slip detection and suppression is proposed. We also present a baseline and feature based approach to detect object slips under illumination and vibration uncertainty. A threshold method is devised to autonomously sample noise in real-time to improve slip detection. Moreover, a fuzzy based suppression strategy using incipient slip feedback is proposed for regulating the grip force. A comprehensive experimental study of our proposed approaches under uncertainty and system for high-performance precision manipulation are presented. We also propose a slip metric to evaluate such performance quantitatively. Results indicate that the system can effectively detect incipient slip events at a sampling rate of 2kHz ($\Delta t = 500\mu s$) and suppress them before a gross slip occurs. The event-based approach holds promises to high precision manipulation task requirement in industrial manufacturing and household services. Comment: 18 pages, 14 figures
Computer Science - Robotics, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Systems and Control, I.2, I.2.9, and I.2.8
Abstract
Robotic vision plays a major role in factory automation to service robot applications. However, the traditional use of frame-based camera sets a limitation on continuous visual feedback due to their low sampling rate and redundant data in real-time image processing, especially in the case of high-speed tasks. Event cameras give human-like vision capabilities such as observing the dynamic changes asynchronously at a high temporal resolution ($1\mu s$) with low latency and wide dynamic range. In this paper, we present a visual servoing method using an event camera and a switching control strategy to explore, reach and grasp to achieve a manipulation task. We devise three surface layers of active events to directly process stream of events from relative motion. A purely event based approach is adopted to extract corner features, localize them robustly using heat maps and generate virtual features for tracking and alignment. Based on the visual feedback, the motion of the robot is controlled to make the temporal upcoming event features converge to the desired event in spatio-temporal space. The controller switches its strategy based on the sequence of operation to establish a stable grasp. The event based visual servoing (EVBS) method is validated experimentally using a commercial robot manipulator in an eye-in-hand configuration. Experiments prove the effectiveness of the EBVS method to track and grasp objects of different shapes without the need for re-tuning. Comment: 8 pages, 10 figures
Awad, Mohammad I., Gan, Dongming, Az-zu'bi, Ali, Thattamparambil, Jaideep, Stefanini, Cesare, Dias, Jorge, and Seneviratne, Lakmal
2016 IEEE International Conference on Robotics and Biomimetics (ROBIO) Robotics and Biomimetics (ROBIO), 2016 IEEE International Conference on. :1808-1813 Dec, 2016
