Design of Near-Optimal Trajectories for the Biped Robot Using MCIWO Algorithm

The present research paper concentrates on the development of optimal trajectories for the foot, hip, and wrist of the biped robot while walking on a flat surface. Cubic polynomial equations are used for generating the foot and wrist trajectories in sagittal plane and hip trajectory in frontal plane. The coefficients of the polynomial trajectories are used as seeds of the invasive weed optimization algorithm. It is important to note that the determination of the boundary conditions of the polynomial equation is a difficult task. To overcome this problem, a new variation of the invasive weed optimization (IWO) algorithm, i.e., modified chaotic invasive weed optimization (MCIWO) algorithm, has been used. Further, the dynamic balance margin (DBM) values obtained in x- and y-directions are compared with the values obtained using the standard IWO algorithm.

[1]  Ju-Jang Lee,et al.  Optimal walking trajectory generation for a biped robot using multi-objective evolutionary algorithm , 2004, 2004 5th Asian Control Conference (IEEE Cat. No.04EX904).

[2]  Fei Chen,et al.  Trajectory planning for biped robot walking on uneven terrain - Taking stepping as an example , 2016, CAAI Trans. Intell. Technol..

[3]  Y. Ramu Naidu,et al.  A hybrid version of invasive weed optimization with quadratic approximation , 2015, Soft Comput..

[4]  Jong Hyeon Park,et al.  Generation of an Optimal Gait Trajectory for Biped Robots Using a Genetic Algorithm , 2004 .

[5]  Václav Snásel,et al.  A modified Invasive Weed Optimization algorithm for time-modulated linear antenna array synthesis , 2010, IEEE Congress on Evolutionary Computation.

[6]  Y. G. Hegazy,et al.  Invasive weed optimization algorithm for solving economic load dispatch , 2016, 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC).

[7]  Jamshid Aghaei,et al.  Application of chaos-based chaotic invasive weed optimization techniques for environmental OPF problems in the power system , 2014 .

[8]  Je Sung Yeon,et al.  Variable walking trajectory generation method for biped robots based on redundancy analysis , 2014 .

[9]  Jinzhao Wu,et al.  A discrete invasive weed optimization algorithm for solving traveling salesman problem , 2015, Neurocomputing.

[10]  Ohung Kwon,et al.  Optimal trajectory generation for a biped robot walking a staircase based on genetic algorithms , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[11]  Ohung Kwon,et al.  Optimal trajectory generation for biped robots walking up-and-down stairs , 2006 .

[12]  Ravi Kumar Mandava,et al.  Study on Influence of Hip Trajectory on the Balance of a Biped Robot , 2017 .

[13]  Ashish Dutta,et al.  Trajectory Generation Using GA for an 8 DOF Biped Robot with Deformation at the Sole of the Foot , 2007, J. Intell. Robotic Syst..

[14]  Evgeni Magid,et al.  Comparison of kinematic and dynamic leg trajectory optimization techniques for biped robot locomotion , 2017 .

[15]  Caro Lucas,et al.  A novel numerical optimization algorithm inspired from weed colonization , 2006, Ecol. Informatics.

[16]  A.A. Kishk,et al.  Invasive Weed Optimization and its Features in Electromagnetics , 2010, IEEE Transactions on Antennas and Propagation.