This chapter focuses on one of the main topics that required to enhance the autonomy of unmanned aerial vehicles (UAVs), namely constrained motion planning (CMP). It first describes motion planning and UAV dynamics and its corresponding internal constraints, and introduces environmental constraints Mission planning of tactical UAVs should be performed while observing terrain and threats. However, regardless of the type or classification of UAV, their general arrangements and configurations in terms of modelling and simulation are usually similar to manned aircraft. The chapter describes the processes for modelling the terrain and threats. It covers three approaches to CMP: a modified particle swarm optimization (PSO) algorithm for offline motion planning, a dynamic hybrid PSO algorithm for real‐time motion planning and the process of multi‐variable‐objective dynamic CMP optimization. Finally, the chapter evaluates the performance of the current off‐line CMP algorithm.


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    Title :

    Constrained Motion Planning and Trajectory Optimization for Unmanned Aerial Vehicles


    Contributors:


    Publication date :

    2017-04-03


    Size :

    35 pages




    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English





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