Generation of stair climbing motion for biped robot  based on combinatorial optimization method

Biped robots are similar to human beings and have broad application prospects in the fields of family service, disaster rescue and military affairs. However, simplified models and fixed center of mass (COM) used in previous research ignore the large-scale stability control ability implied by whole-body motion. The present paper proposed a two-level controller based on a simplified model and whole-body dynamics. In high level, a model predictive control (MPC) controller is implemented to improve zero moment point (ZMP) control performance. In low level, a quadratic programming optimization method is adopted to realize trajectory tracking and stabilization with friction and joint constraints. The simulation shows that a 12-degree-of-freedom force-controlled biped robot model, adopting the method proposed in this paper, can recover from a 40 Nm disturbance when walking at 1.44 km/h without adjusting the foot placement, and can walk on an unknown 4 cm high stairs and a rotating slope with a maximum inclination of 10°. The method is also adopted to realize fast walking up to 6 km/h.

Download Full-text

Combinatorial Optimization Method for Parts Matching in a Precision Assembly System Using Selective Assembly and Micro-Machining.

Journal of the Japan Society for Precision Engineering ◽

10.2493/jjspe.65.1579 ◽

1999 ◽

Vol 65 (11) ◽

pp. 1579-1583 ◽

Cited By ~ 2

Author(s):

Yasuhiro YAMADA ◽

Yoshiaki KOMURA ◽

Junnosuke MIZUTANI ◽

Ikuo TANABE

Keyword(s):

Combinatorial Optimization ◽

Optimization Method ◽

Assembly System ◽

Micro Machining ◽

Selective Assembly

Download Full-text

Combinatorial Optimization Method Using Distance in Scheduling Problem

2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC) ◽

10.1109/smc.2018.00210 ◽

2018 ◽

Author(s):

Keiichiro Yasuda ◽

Junichi Tsuchiya ◽

Kenichi Tamura ◽

Yuta Obinata

Keyword(s):

Combinatorial Optimization ◽

Optimization Method ◽

Scheduling Problem

Download Full-text

Combinatorial Optimization Method Considering Distance in Scheduling Problem

Proceedings of the Tenth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2018) - Advances in Intelligent Systems and Computing ◽

10.1007/978-3-030-17065-3_15 ◽

2019 ◽

pp. 147-157

Author(s):

Yuta Obinata ◽

Kenichi Tamura ◽

Junichi Tsuchiya ◽

Keiichiro Yasuda

Keyword(s):

Combinatorial Optimization ◽

Optimization Method ◽

Scheduling Problem

Download Full-text

A novel online gait optimization approach for biped robots with point-feet

ESAIM Control Optimisation and Calculus of Variations ◽

10.1051/cocv/2017034 ◽

2019 ◽

Vol 25 ◽

pp. 81

Author(s):

Majid Anjidani ◽

M.R. Jahed Motlagh ◽

M. Fathy ◽

M. Nili Ahmadabadi

Keyword(s):

Learning Algorithm ◽

Biped Robot ◽

Optimization Method ◽

Optimization Approach ◽

Loop Model ◽

Modeling Error ◽

Environment Change ◽

Biped Robots ◽

Walking Gait ◽

New Situation

Designing a stable walking gait for biped robots with point-feet is stated as a constrained nonlinear optimization problem which is normally solved by an offline numerical optimization method. On the result of an unknown modeling error or environment change, the designed gait may be ineffective and an online gait improvement is impossible after the optimization. In this paper, we apply Generalized Path Integral Stochastic Optimal Control to closed-loop model of planar biped robots with point-feet which leads to an online Reinforcement Learning algorithm to design the walking gait. We study the ability of the proposed method to adapt the controller of RABBIT, which is a planar biped robot with point-feet, for stable walking. The simulation results show that the method, starting a dynamically unstable initial gait, quickly compensates the modeling error and reaches to a walking with exponential stability and desired features in a new situation which was impossible by the past methods.

Download Full-text