Advanced UAV Trajectory Generation: Planning and Guidance

As technology and legislation move forward (JAA & Eurocontrol, 2004) remotely controlled, semi-autonomous or autonomous Unmanned Aerial Systems (UAS) will play a significant role in providing services and enhancing safety and security of the military and civilian community at large (e.g. surveillance and monitoring) (Coifman et al., 2004). The potential market for UAVs is, however, much bigger than just surveillance. UAVs are ideal for risk assessment and neutralization in dangerous areas such as war zones and regions stricken by disaster, including volcanic eruptions, wildfires, floods, and even terrorist acts. As they become more autonomous, UAVs will take on additional roles, such as air-to-air combat and even planetary science exploration (Held et al., 2005). As the operational capabilities of UAVs are developed there is a perceived need for a significant increase in their level of autonomy, performance, reliability and integration with a controlled airspace full of manned vehicles (military and civilian). As a consequence researchers working with advanced UAVs have moved their focus from system modeling and low-level control to mission planning, supervision and collision avoidance, going from vehicle constraints to mission constraints (Barrientos et al., 2006). This mission-based approach is most useful for commercial applications where the vehicle must accomplish tasks with a high level of performance and maneuverability. These tasks require flexible and powerful trajectory-generation and guidance capabilities, features lacking in many of the current commercial UAS. For this reason, the purpose of this work is to extend the capabilities of commercially available autopilots for UAVs. Civil systems typically use basic trajectory-generation algorithms, capable only of linear waypoint navigation (Rysdyk, 2003), with a minimum or non-existent control over the trajectory. These systems are highly constrained when maneuverability is a mission requirement. On the other hand, military researchers have developed algorithms for high-performance 3D path planning and obstacle avoidance (Price, 2006), but these are highly proprietary technologies that operate with different mission constraints (target acquisition, threat avoidance and situational awareness) so they cannot be used in civil scenarios. This chapter presents a robust Trajectory Generation and Guidance Module (TG2M), a software tool capable of generating complex six-degrees-of-freedom trajectories in 3D space with velocity, acceleration, orientation and time constraints. The TG2M is an extension module to the Aerial Vehicle Control Language (AVCL), a software architecture and