Design, Analysis, and Control of a Spring-Assisted Modular and Reconfigurable Robot

Conventional robot manipulators produce poor payload to weight ratio and limited manipulation ability, as a significant portion of available actuation force is used to balance their own weight. The same cause also limits the robot's operation capability in terms of acceleration and manipulation force. Such problems become more severe for modular and reconfigurable robots (MRRs) when they are expanded by adding predesigned modules. Static balancing with counterweights and external springs can greatly improve a robot's payload and manipulation capabilities, but require sophisticated mechanisms and restrict the working envelope of the robot. In this paper, an innovative spring-assisted MRR design and control framework is presented, which is developed based on a synergetic integration of robot control with a brake and an embedded spring at each modular joint. The spring is inserted between the brake and the motor shaft through a decoupling bearing. By activating the brake, static balancing can be established at any desirable position of each module and any configuration of the robot, allowing reinforced delicate operation in a neighborhood of the balanced configuration such as door opening, as well as spring-assisted lift of heavy payload. A distributed control method has been proposed to facilitate control of the spring-assisted MRRs, which does not rely on a priori dynamic models, and can suppress uncertainties caused by reconfigurations, eliminating the need to readjust control parameters of the lower modules when new modules are added or removed. Prototype modules have been developed, and the experimental results have confirmed the effectiveness of the proposed design and control.

[1]  Guang Chen,et al.  Kernel for Modular Robot Applications: Automatic Modeling Techniques , 1999, Int. J. Robotics Res..

[2]  Wen-Hong Zhu,et al.  Adaptive Control of Harmonic Drives Based on Virtual Decomposition , 2006, IEEE/ASME Transactions on Mechatronics.

[3]  Markus Schedl,et al.  Torque-Controlled Lightweight Arms and Articulated Hands: Do We Reach Technological Limits Now? , 2004, Int. J. Robotics Res..

[4]  Clément Gosselin,et al.  Static balancing of 3-DOF planar parallel mechanisms , 1999 .

[5]  Wen-Hong Zhu,et al.  Modular Robot Manipulators with Preloadable Modules , 2007, 2007 International Conference on Mechatronics and Automation.

[6]  Guangjun Liu,et al.  Comparative Study of Robust Saturation-Based Control of Robot Manipulators: Analysis and Experiments , 1996, Int. J. Robotics Res..

[7]  Andrew A. Goldenberg,et al.  Robust control of robot manipulators based on dynamics decomposition , 1997, IEEE Trans. Robotics Autom..

[8]  Mark Moll,et al.  Modular Self-reconfigurable Robot Systems: Challenges and Opportunities for the Future , 2007 .

[9]  Guangjun Liu,et al.  Decomposition-based friction compensation of mechanical systems , 2002 .

[10]  Andrew A. Goldenberg,et al.  Precise slow motion control of a direct-drive robot arm with velocity estimation and friction compensation , 2004 .

[11]  Carlos Canudas de Wit,et al.  A survey of models, analysis tools and compensation methods for the control of machines with friction , 1994, Autom..

[12]  Guangjun Liu,et al.  Interaction Analysis and Online Tip-Over Avoidance for a Reconfigurable Tracked Mobile Modular Manipulator Negotiating Slopes , 2010, IEEE/ASME Transactions on Mechatronics.

[13]  Guangjun Liu,et al.  Uncertainty decomposition-based robust control of robot manipulators , 1996, IEEE Trans. Control. Syst. Technol..

[14]  Wen-Hong Zhu,et al.  Modular Robot Manipulators Based on Virtual Decomposition Control , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[15]  Guangjun Liu,et al.  Distributed control of modular and reconfigurable robot with torque sensing , 2008, Robotica.

[16]  Andrew A. Goldenberg,et al.  Neurofuzzy control of modular and reconfigurable robots , 2003 .

[17]  Liviu Ciupitu,et al.  The static balancing of the industrial robot arms: Part II: Continuous balancing , 2000 .

[18]  Sunil Kumar Agrawal,et al.  Reactionless robots: novels designs and concept studies , 2002, 7th International Conference on Control, Automation, Robotics and Vision, 2002. ICARCV 2002..

[19]  Guilin Yang,et al.  Automatic Model Generation for Modular Reconfigurable Robot Dynamics , 1998 .

[20]  Bin Li,et al.  Reconfiguration of a Group of Wheel-Manipulator Robots Based on MSV and CSM , 2009, IEEE/ASME Transactions on Mechatronics.

[21]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[22]  Yangmin Li,et al.  Real-Time Tip-Over Prevention and Path Following Control for Redundant Nonholonomic Mobile Modular Manipulators via Fuzzy and Neural-Fuzzy Approaches , 2006 .

[23]  Mathukumalli Vidyasagar,et al.  A new parallelogram linkage configuration for gravity compensation using torsional springs , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[24]  Liviu Ciupitu,et al.  The static balancing of the industrial robot arms , 2000 .

[25]  Gregory S. Chirikjian,et al.  Modular Self-Reconfigurable Robot Systems [Grand Challenges of Robotics] , 2007, IEEE Robotics & Automation Magazine.