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Due to redundancy and natural instability of humanoid robots, their motion planning becomes a challenging task. Designing stable gaits with smooth trajectories for a humanoid robot is the main goal of this article. Taking all related parameters on robot's walking into consideration, a new gait planning approach in the task space is developed. Various aspects like upper-body motion and stability requirements have the most significant role in this new gait planning process. In order to reduce undesired fluctuations on robot center of mass a new method in trajectory planning is also suggested. To show performance of the proposed algorithm, it is compared with another reliable approach in this field, and the results will be discussed. [ABSTRACT FROM PUBLISHER]

Proper performance of biped robots in various indoor environment conditions depends on reliable landmark detection and self-localization. Probabilistic approaches are among the most capable methods to present a real-time and inclusive solution for biped robot's localization. This paper focuses on the newly proposed odometry system implementing the kinematic model, predictive estimator of the camera position, particle filter methods such as Monte Carlo Localization (MCL) and Augmented MCL with utilization of landmarks, lines, points, and optimized filtering parameters for robots' state estimation. Moreover, kidnap scenarios which could not be considered and handled with the uni-modal Kalman filter-based techniques, are studied here for the Nao biped robots on the RoboCup standard platform league's soccer filed. Experimental data are employed to evaluate effectiveness and performance of the proposed vision module and augmented MCL scheme. [ABSTRACT FROM PUBLISHER]

In some applications, biped robots are preferred to wheeled robots since biped robots are able to move in various environments with different conditions. However, stable walking for biped robots is a challenging issue. Various approaches have been developed to improve these robots performance. In this paper, we first introduce a different mechanical design of biped robots based on parallel mechanism and then compare it with conventional design of robots. Then we formulate dynamic equations of this biped robot and generate some trajectories for the joints. Finally, the proposed design is validated by experimental results. [ABSTRACT FROM PUBLISHER]

The dynamic walking stability of robots is a key to biped robots study. Due to the uncertainty of outside environment, adaptability has become a priority in the research of dynamic walking of robots. In order to realize the dynamic walking of robots, a Genetic Neural Network is used to develop an Adaptive Control Neural Network. A better walking result is realized by the Neural Network trained by abnormal walking samples and self-adaptive fitness formulation. [ABSTRACT FROM PUBLISHER]