17Constrained Motion Planning and Trajectory Optimization for Unmanned Aerial Vehicles
Seid H. Pourtakdoust1 and Jalal Karimi2
1 Center for Research and Development in Space Science and Technology, Sharif University of Technology, Tehran, Iran
2 Space Research Institute, MUT, Tehran, Iran
17.1 Introduction
Increasing complexity and advances in hardware and software technologies within the realms of control, robotics, electronics and artificial intelligence have led to the enhanced design, development and utility of unmanned air vehicles (UAVs) in a wide range of applications. Improvements in the level of autonomy, effective decision‐making with reduced workload, reduction of human user/operator errors, as well as increases in the operating range of UAVs are considered highly desirable. This chapter is devoted to one of the main topics required to enhance the autonomy of UAVs, namely constrained motion planning (CMP).
This chapter is arranged as follows: motion planning is described in Section 17.1. Section 17.2 is devoted to UAV dynamics and its corresponding internal constraints. Environmental constraints are introduced in Section 17.3. Sections 17.4–17.6 cover three approaches to CMP: a modified particle swarm optimization algorithm for offline motion planning is described in Section 17.4, Section 17.5 develops a dynamic hybrid particle swarm optimization algorithm for real‐time motion planning and the process of multi‐variable‐objective dynamic CMP optimization is discussed in ...
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