Optimization of Motion Planning for Quadrotor-Equipped Robotic Manipulators

The focus of the work is on optimizing motion planning for quadcopter-equipped robotic manipulators by integrating quadcopter design, modeling, and path planning for a robotic arm mounted on a quadcopter through MATLAB. Recently, quadcopters have also been used in many application fields with increased viability. This paper will attempt at bringing a complete framework that enhances the operational capabilities of quadcopters through optimized path planning algorithms. The approach will rely on obstacle avoidance techniques for safe operation with satisfactory efficiency in unstructured environments. Advanced algorithms such as Rapidly-exploring Random Trees and dynamic window approaches provide solutions to this challenge of redundancy in the path followed and adaptability in its surroundings. Simulations prove that the proposed optimization methods strongly improve the accuracy and efficiency of the path planned by the robotic arm as it adheres to the dynamic constraints imposed. This work can apply practical insight into many real-world fields such as logistics, surveillance, and search-and-rescue applications aside from contributing to the theoretical understanding of quadcopter dynamics.