Parallel-kinematics machine design for submicron and meso-scale manipulation

• Main Authors: Chen, I-Ming., Yeo, Song Huat., Li, Chuan.
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Research Report
• Language: English
• Published: 2010
• Subjects: DRNTU::Engineering::Mechanical engineering::Kinematics and dynamics of machinery
• Online Access: http://hdl.handle.net/10356/42254
• Institution: Nanyang Technological University

Parallel-Kinematics Machines (PKM) are mechanical systems that have a multidegree-of-freedom platform connected with a number of actuating arms in parallel geometry. Such kind of mechanical systems may possess high force loading capacity and fine dexterous motion characteristics at the same time due to the closed-loop structure. This project aims at developing new PKM design methodologies for submicron- and meso-scale manipulation tasks that arise in biomedical engineering and photonics. For meso-scale parallel manipulation, the concept of joint-coupling (JC) is proposed and studied in the project. The idea behind JC is to couple the movement of several joints together with a single actuator by mechanical or electronic means while preserving the mobility of the manipulator. In this work, planar PMs with JCs are studied to illustrate the advantage of this approach for singularity management. In selecting appropriate coupling coefficients, two methods are proposed: (1) the taskbased approach, which uses kinematic property of the manipulator, (2) the motor torque limit approach, which requires the dynamic model of the manipulator. Simulation and experiment results indicate that the both methods are effective for managing manipulator singularities. Both mechanical and electronic coupling devices are developed for experiments. In addition to joint-coupling, the decoupled parallel manipulator geometry based on screw theory is investigated for meso-scale manipulation. Design guidelines, and workspace generation are studied systematically. These two design methods will have impact on future parallel manipulation design and applications.