A unified design for lightweight robotic arms based on unified description of structure and drive trains

This article presents a unified design for lightweight robotic arms based on a unified description of structure and drive trains. In the unified design, the drive trains and structural dimensions are parameterized as design variables, and a major objective minimizes the total mass of robotic arms satisfying the constraint conditions and design criteria. To implement the optimization problem, a mapping relationship between mass and torque of drive trains is introduced as their power–density curves, which enable a unified description of structure and drive trains combining with the dynamics of robotic arms. In this implementation of unified design, there are two modules: structure optimization and drive trains design. The finite element method with nonlinear programming by quadratic Lagrange algorithm is adopted to implement the structure optimization. Moreover, the dynamic analysis in MSC ADAMS is achieved to design the drive trains of robotic arms. This method could uniformly evaluate all components of robotic arms in mass and continuously search the global optimal results. Finally, a design example on this unified design is compared with a referenced design to illustrate the validity and advantage of the proposed scheme.

[1]  Alin Albu-Schäffer,et al.  On a new generation of torque controlled light-weight robots , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[2]  Albert Albers,et al.  Integrated structural and controller optimization for lightweight robot design , 2009, 2009 9th IEEE-RAS International Conference on Humanoid Robots.

[3]  Mingchang He,et al.  An overall structure optimization for a light-weight robotic arm , 2016, 2016 IEEE 11th Conference on Industrial Electronics and Applications (ICIEA).

[4]  F. Farelo,et al.  Design, simulation and testing of a new modular wheelchair mounted robotic arm to perform activities of daily living , 2009, 2009 IEEE International Conference on Rehabilitation Robotics.

[5]  Lelai Zhou,et al.  A New Approach to Design of a Lightweight Anthropomorphic Arm for Service Applications , 2015 .

[6]  Alin Albu-Schäffer,et al.  DLR's torque-controlled light weight robot III-are we reaching the technological limits now? , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[7]  Jun-Hyuk Choi,et al.  Design of axial flux permanent magnet brushless DC motor for robot joint module , 2010, The 2010 International Power Electronics Conference - ECCE ASIA -.

[8]  C. Gosselin.  The optimum design of robotic manipulators using dexterity indices , 1992, Robotics Auton. Syst..

[9]  Brian Rooks.  The harmonious robot , 2006, Ind. Robot.

[10]  Hyun Min Do,et al.  Design of an modular actuation module for a dual arm robot manipulator , 2012, 2012 9th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI).

[11]  Panos S. Shiakolas,et al.  Optimum Robot Design Based on Task Specifications Using Evolutionary Techniques and Kinematic, Dynamic, and Structural Constraints , 2002 .

[12]  Michael Rygaard Hansen,et al.  Integrated dimensional and drive-train design optimization of a light-weight anthropomorphic arm , 2012, Robotics Auton. Syst..

[13]  Marcus Pettersson,et al.  Drive Train Optimization for Industrial Robots , 2009, IEEE Transactions on Robotics.

[14]  Qiang Huang,et al.  Mechanical design of a light weight and high stiffness humanoid arm of BHR-03 , 2009, 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[15]  Fredrik Roos,et al.  Towards a methodology for integrated design of mechatronic servo systems , 2007 .

[16]  M. Gautier,et al.  Optimum Choice of Robot Actuators , 1990 .

[17]  Shang Jing,et al.  Structure optimization for brushless DC motor in robot's arms using FEM , 2007, 2007 International Conference on Electrical Machines and Systems (ICEMS).

[18]  Klaus Schittkowski,et al.  NLPQL: A fortran subroutine solving constrained nonlinear programming problems , 1986 .