Abstract
Biped robots are inherently unstable because of their complex kinematics as well as dynamics. Despite many research efforts in developing biped locomotion, the performance of biped locomotion is still far from the expectations. This paper proposes a model-based framework to generate stable biped locomotion. The core of this framework is an abstract dynamics model which is composed of three masses to consider the dynamics of stance leg, torso, and swing leg for minimizing the tracking problems. According to this dynamics model, we propose a modular walking reference trajectories planner which takes into account obstacles to plan all the references. Moreover, this dynamics model is used to formulate the controller as a Model Predictive Control (MPC) scheme which can consider some constraints in the states of the system, inputs, outputs, and also mixed input-output. The performance and the robustness of the proposed framework are validated by performing several numerical simulations using MATLAB. Moreover, the framework is deployed on a simulated torque-controlled humanoid to verify its performance and robustness. The simulation results show that the proposed framework is capable of generating biped locomotion robustly.
Highlights
Humanoid robots are more adapted to our real environment for helping us to perform our daily-life tasks
We propose a modular framework to generate a robust biped locomotion which takes into account the dynamics of torso and swing leg
To validate the portability and platform-independency of the proposed framework and to show the performance of the framework in controlling a full humanoid robot, we performed a set of simulations using a simulated COMAN humanoid in the Gazebo simulator which is an open-source simulation environment developed by the Open Source Robotics Foundation (OSRF)
Summary
Humanoid robots are more adapted to our real environment for helping us to perform our daily-life tasks. Developing a robust walking framework for humanoid robots has been researched for decades, and it is still a challenging problem in the robotics community The complexity of this problem derives from several different aspects like considering an accurate hybrid dynamics model, designing appropriate controllers, and formulating suitable reference trajectory planners. We deploy the framework on a full-size simulated torque-controlled humanoid robot and conduct a set of simulations to validate its robustness, performance and portability In this framework, the overall dynamics of the robot is modeled using a three-mass model which takes into account dynamics of the legs and the torso.
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