TAF PUBLISHING

Humanoid robots are extensively becoming an essential part of the social life with the development and implementation of Human-Like behaviors such as walking, grasping, standing up, and sitting down. For generating natural Human-Like behaviors, the desired motion should be controlled properly in the dynamic and unstructured environments. This paper presents a Sit-to-Stand (STS) motion algorithm developed to lead autonomous Human-Like motion. The proposed algorithm has two main steps; where in the first one, horizontal distances of the humanoid robot for sitting down or standing up motions are identified to determine the corresponding joint angles, and in the second stage, the initial joint angles of the robot have been driven to the target joint angle states. Although this algorithm can be adopted to all humanoid robots, in this paper, it has been specifically applied to the NAO humanoid robot. Results show that the NAO humanoid robot is able to autonomously achieve halfway standing up and sitting down from chairs having heights between 9.5 and 11.5 cm. The developed STS algorithm will be combined with chair recognition and selection algorithms in the future, which will significantly enhance the capabilities of autonomous humanoid robots.