Analysis and Energy Reduction of Humanoid Robot Motions – Stand Up and Sit Down

This research studies the electrical power reduction and control analysis of various motion tasks of a humanoid robot. These motions include standing up and sitting down. Each motion’s tasks have their stable and unstable phases throughout the complete motion cycle. Unstable phases can be caused by gravity forces and improper handling of the upper body of the humanoid robot leaning too forward or backward. Even though most of the dynamic motions seem to be accomplished very simply by humans; standing up and sitting down could create challenges for humanoid robots. Some of the critical challenges researches face are: dynamic nature of motions, humanoid robot joint coordination, whole body balance, stability of the model, limited energy source, energy saving techniques and modeling. Dynamic motions of humanoid robots can be modeled and analyzed to reduce electrical power use. In order to accomplish such energy savings, a researcher needs to study the kinematics, dynamics of a humanoid, and motion tasks with given constraints. The robot in this research is modeled as a planar humanoid robot. All motion tasks of a humanoid robot are characterized in terms of motion variables. These motion variables include joint angular positions, joint angular velocity, joint angular acceleration, humanoid robot center of mass (CoM) position, velocity and acceleration change and center of pressure (CoP) position change. All mathematical models are completed so that electrical power analysis of each task produce comparable results. Humanoid robot joint cost functions related to energy consumption are used to define joint input electrical power used, joint mechanical power used, joint mechanical power dispersion and joint power loss due to torque required. In this research, a 4-link 3-joint humanoid is modeled for standing up and sitting down tasks. For each task, kinematics and dynamics models are created, motion constraints are found, energy and power usage analysis for whole robot and for individual joint motors are accomplished. By finding the best energy usage per motion variable, humanoid robot used less input electrical power to accomplish the motion task