Modified type-2 fuzzy controller for intercollision avoidance of single and multi-humanoid robots in complex terrains

• Published in: Intelligent service robotics Vol. 16; no. 1; pp. 87 - 108
• Main Authors: Kashyap, Abhishek Kumar, Parhi, Dayal R.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2023; Springer Nature B.V
• Subjects: Algorithms; Ant colony optimization; Artificial Intelligence; Barriers; Collision avoidance; Control; Controllers; Dining Philosophers Problem; Dynamical Systems; Efficiency; Engineering; Fuzzy control; Genetic algorithms; Humanoid; Mechatronics; Navigation; Original Research Paper; Path planning; Philosophers; Robotics; Robotics and Automation; Robots; Route optimization; Sensors; Simulation; Travel time; User Interfaces and Human Computer Interaction; Vibration; Type-2 fuzzy controller; Ant colony optimization; Multi-humanoid NAOs; Navigation; Dining philosopher controller
• ISSN: 1861-2776; 1861-2784
• DOI: 10.1007/s11370-022-00448-0

The path planning methodology followed by the humanoid robots generally focuses on the improvisation of path length and travel time in completing assigned tasks. The overall computational cost decreases when the robot is guided to the target with minimum path length and travel time. This can be achieved by hybridizing two algorithms. In this paper, the navigational controller of the humanoid robots is based on the hybridization of the Type-2 fuzzy system and the adaptive ant colony optimization (AACO) method. The proposed hybridized technique cumulates the global search Type-2 fuzzy controller with the local improvisation AACO method for efficient path planning. The localization system as an input to the Type-2 fuzzy controller provides global positioning of the obstacles and the target in the unknown terrain. Type-2 fuzzy controller algorithm specifies the initial direction vector to guide the robot to the target based on the IF–THEN rule. If the robot encounters an obstacle in its path, the Type-2 fuzzy controller provides an initial turning angle, which is the input to the AACO. It gives an optimized turning angle, which further refines the direction vector. The proposed controller is demonstrated in a single and multi-humanoid robot system. Single and multiple humanoid robots are placed in various static complex terrains with unique targets for all of them to reach. Due to the possibility of inter-collision among humanoid robots in the muti-humanoid system, a novel dining philosopher controller is employed to solve the conflicting scenario with an optimized solution. Simulations and experiments are carried out on the single and multi-humanoid system based on the proposed hybridized approach yields efficient and collision-free navigation with a proper conformation between the results under 5%. The proposed technique has been compared with the previously developed approach for navigation of the humanoid robot based on travel time. In comparison, it proves to be sufficiently efficient and robust for the path planning of the humanoid robot in complex terrains.