**7. Conclusions**

We have studied optimization-based motion simulation with modular waist and knee exoskeleton robot as an assistive force. We used Denavit-Hartenberg method for kinematics, Lagrange's equations of motion with external force and moment term, B-spline function approximation. In motion simulation, the performance measure is mechanical energy which is presented as the summation of joint torque squares. Minimal constraints are applied such as joint angle limits, torque limits, dynamic balance, and hand/foot positions., the optimization process find out the minimized energy consumed motion under the assistive forces from the modular waist and knee exoskeleton robots which are applied during the weight lifting motion.

This method provides unique feature with human-exoskeleton modeling and simulation area. It can give us predictive motion of human so that the exoskeleton parameters are adjusted based on the predicted motion simulation. Also, human motion can be generated automatically for the control algorithm of robot to collaborate with human. It can be used as evaluation and assessment tool for the design parameters of exoskeleton robot development in any given tasks according to human factors. Furthermore, this can reduce the development cost of exoskeleton because not many prototypes are necessary and provides safe design and test process during the exoskeleton development procedure. Of course, the musculoskeletal model should be developed for more accurate calculation of human factors and it will be remained as future works.
