Improved Damped Least Squares Solution with Joint Limits, Joint Weights and Comfortable Criteria for Controlling Human-like Figures

In order to generate natural posture and motion of virtual human-like figures, damped least squares inverse kinematics method is modified. Physical rules of human being like joint limits, joint weights and comfortable criteria are introduced to the design of damping factors for the improved damped least squares solution. The proposed method performs well on guaranteeing joint limit avoidance and producing natural-looking postures. This new scheme is successfully implemented and tested for real-time control of a seven-degree-of-freedom virtual human skeletal upper limb. Experiment results show that the improved solution is more robust and stable than the original damped least squares method.

[1]  Samy F. M. Assal Neural network learning from hint for the cyclic motion of the constrained redundant arm , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[2]  Yoshihiko Nakamura,et al.  Inverse kinematic solutions with singularity robustness for robot manipulator control , 1986 .

[3]  Stefano Chiaverini,et al.  A damped least-squares solution to redundancy resolution , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[4]  S. Buss Introduction to Inverse Kinematics with Jacobian Transpose , Pseudoinverse and Damped Least Squares methods , 2004 .

[5]  Samuel R. Buss,et al.  Selectively Damped Least Squares for Inverse Kinematics , 2005, J. Graph. Tools.

[6]  Daniel E. Whitney,et al.  Resolved Motion Rate Control of Manipulators and Human Prostheses , 1969 .

[7]  Nak Young Chong,et al.  Inverse kinematics learning by modular architecture neural networks with performance prediction networks , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[8]  S. Chiaverini,et al.  Achieving user-defined accuracy with damped least-squares inverse kinematics , 1991, Fifth International Conference on Advanced Robotics 'Robots in Unstructured Environments.

[9]  Lorenzo Sciavicco,et al.  Robust Control of Robotic Manipulators , 1984 .

[10]  Chih-Cheng Chen,et al.  A combined optimization method for solving the inverse kinematics problems of mechanical manipulators , 1991, IEEE Trans. Robotics Autom..

[11]  A. Liegeois,et al.  Automatic supervisory control of the configuration and behavior of multi-body mechanisms , 1977 .

[12]  W. Wolovich,et al.  A computational technique for inverse kinematics , 1984, The 23rd IEEE Conference on Decision and Control.

[13]  Charles W. Wampler,et al.  Manipulator Inverse Kinematic Solutions Based on Vector Formulations and Damped Least-Squares Methods , 1986, IEEE Transactions on Systems, Man, and Cybernetics.

[14]  Éric Marchand,et al.  A redundancy-based iterative approach for avoiding joint limits: application to visual servoing , 2001, IEEE Trans. Robotics Autom..

[15]  Rajiv V. Dubey,et al.  A weighted least-norm solution based scheme for avoiding joint limits for redundant joint manipulators , 1993, IEEE Trans. Robotics Autom..