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

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Abstract

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.

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Acknowledgements

This study is not financed.

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Authors and Affiliations

  1. Mechanical Engineering Department, Robotics Laboratory, MIT Art, Design & Technology University, Pune, 412201, Maharashtra, India

    Abhishek Kumar Kashyap

  2. Mechanical Engineering Department, Robotics Laboratory, National Institute of Technology, Rourkela, 769008, Odisha, India

    Dayal R. Parhi

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Contributions

Conceptualization was contributed by AKK, DRP. Methodology was contributed by AKK, DRP– Software was contributed by AKK;– Investigation was contributed by AKK;– Formal Analysis was contributed by AKK, DRP – Validation was contributed by AKK;– Data curation was contributed by AKK– Writing—original draft was contributed by AKK;– Writing—review and editing was contributed by AKK, DRP – Visualization was contributed by AKK, DRP – Resources were contributed by AKK– Project administration was contributed by AKK, DRP – Supervision was contributed by DRP

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Correspondence to Abhishek Kumar Kashyap.

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Kashyap, A.K., Parhi, D.R. Modified type-2 fuzzy controller for intercollision avoidance of single and multi-humanoid robots in complex terrains. Intel Serv Robotics 16, 87–108 (2023). https://doi.org/10.1007/s11370-022-00448-0

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