Towards Algorithms for Effective Stabilization and Situational Awareness for Humanoid Robots

Abstract

Algorithms and operating systems are continually being evolved in need to develop more equipped and reliable robotic systems capable of performing in many real-world dynamics. The NAO robot is used to observe the ability of robots to perform specific tasks and the accuracy and reliability in the robot’s performance. The robot is tasked with stepping onto a scaled platform, maintaining stability when pushed, and accurately identifying object distances. Algorithms modeled using Fuzzy Petri nets, a graphical simulation and demonstration tool, are made to improve these efforts leading to effective stabilization and situational awareness, which can effectively lead to a more independent model.