Work

MorphoMove: Bi-Modal Path Planner with MPC-based Path Follower for Multi-Limb Morphogenetic UAV

Year: 2024

Type: conference-paper

Abstract: This paper discusses developments for a multi-limb morphogenetic UAV, MorphoGear, that is capable of both aerial flight and ground locomotion. A hybrid path planning algorithm based on the A* strategy has been developed, enabling seamless transition between air-to-ground navigation modes, thereby enhancing robot's mobility in complex environments. Moreover, precise path following is achieved during ground locomotion with a Model Predictive Control (MPC) architecture for its novel walking behaviour. Experimental validation was conducted in the Unity simulation environment utilizing Python scripts to compute control values. The algorithm's performance is validated by the Root Mean Squared Error (RMSE) of 0.91 cm and a maximum error of 1.85 cm, as demonstrated by the results. These developments highlight the adaptability of MorphoGear in navigation through cluttered environments, establishing it as a usable tool in autonomous exploration, both aerial and ground-based.

Source: Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics

DOI: 10.1109/smc54092.2024.10831196

Authors: Muhammad Ahsan Mustafa, Yasheerah Yaqoot, Mikhail Martynov, Sausar Karaf, Dzmitry Tsetserukou

Institution: Skolkovo Institute of Science and Technology

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: Russell Sage Foundation, Russian Science Foundation

Awards: G1267233886, G2841149998