Modelling of Walking Humanoid Robot With Capability of Floor Detection and Dynamic Balancing Using Colored Petri Net
This addresses the challenge of complex humanoid robot control for robotics researchers, but it appears incremental as it combines existing sensors and image processing without major breakthroughs.
The paper tackled the problem of controlling humanoid robots by presenting a general algorithm using Colored Petri Nets for dynamic balancing and floor detection, achieving a high-level operational model.
Most humanoid robots have highly complicated structure and design of robots that are very similar to human is extremely difficult. In this paper, modelling of a general and comprehensive algorithm for control of humanoid robots is presented using Colored Petri Nets. For keeping dynamic balance of the robot, combination of Gyroscope and Accelerometer sensors are used in algorithm. Image processing is used to identify two fundamental issues: first, detection of target or an object which robot must follow; second, detecting surface of the ground so that walking robot could maintain its balance just like a human and shows its best performance. Presented model gives high-level view of humanoid robot's operations.