Lee, Jongwoo Oh, Yonghwan Minh Nhat Vu 2024-01-19T11:08:11Z 2024-01-19T11:08:11Z 2022-02-28 2017-05 https://pubs.kist.re.kr/handle/201004/114646 In this paper, we present a control method for bipedal robotic walking with compliant legs and upright trunk. The proposed method is validated with dynamic simulation of a planar, reduced-order biped walking model, consisting of a rigid trunk and compliant legs. Existing literatures have found that simple mass-spring model can describe dynamic characteristics of bipedal locomotion, in terms of Ground Reaction Force (GRF) and the Center of Mass (CoM) profile. In order to explain trunkupright walking mechanics, a control method named the Virtual Pivot Point (VPP) method based on the Virtual Pendulum (VP) concept has been previously introduced. In this method, the axial force of a compliant leg is redirected towards the VPP of the model, which is located above the CoM of the model, in order to provide restoring moment about trunk motion. The resulting behaviour of the model would resemble a virtual pendulum rotating about the VPP, thus upright trunk while walking is pursued. However, we have found that for some cases this method provides upsetting moment, instead of restoring moment, which degrades the performance of the control. Inspired from this analysis, we propose a new force- redirecting method as a controller for robotic biped walking. We consider a dynamic simulation of a simple, planar simple walking model to validate the performance of the proposed method under random initial condition and under the presence of force disturbance. The proposed method shows stable and robust walking performance compared to the VPP method. English IARIA XPS PRESS A Control Method for Bipedal Trunk Spring Loaded Inverted Pendulum Model Conference 1 13th International Conference on Autonomic and Autonomous Systems (ICAS), pp.24 - 29 13th International Conference on Autonomic and Autonomous Systems (ICAS) 24 29 US Barcelona, SPAIN 2017-05-21 THIRTEENTH INTERNATIONAL CONFERENCE ON AUTONOMIC AND AUTONOMOUS SYSTEMS (ICAS 2017) 000428763400005