Walking of the iCub humanoid robot in different scenarios: implementation and performance analysis
This work addresses the challenge of enabling walking on the iCub robot for researchers, but it is incremental as it applies existing methods to new hardware without major innovations.
The authors implemented walking motions on the iCub humanoid robot using extensions of classic techniques like ZMP-based pattern generation and position control, analyzing its capabilities and limitations across different walking tasks to provide performance references for users.
The humanoid robot iCub is a research platform of the Fondazione Istituto Italiano di Tecnologia (IIT), spread among different institutes around the world. In the most recent version of iCub, the robot is equipped with stronger legs and bigger feet, allowing it to perform balancing and walking motions that were not possible with the first generations. Despite the new legs hardware, walking has been rarely performed on the iCub robot. In this work the objective is to implement walking motions on the robot, from which we want to analyze its walking capabilities. We developed software modules based on extensions of classic techniques such as the ZMP based pattern generator and position control to identify which are the characteristics as well as limitations of the robot against different walking tasks in order to give the users a reference of the performance of the robot. Most of the experiments have been performed with HeiCub, a reduced version of iCub without arms and head.