Reactive Obstacle Avoidance of UAVs with Dynamic Inversion Based Partial Integrated Guidance and Control

Abstract

Unlike existing literature on obstacle avoidance of UAVs that mainly propose only guidance techniques (using either kinematic or, at best, point-mass models), an innovative partial integrated guidance and control (PIGC) technique is presented in this paper for reactive obstacle avoidance of UAVs that uses the Six-DOF flight dynamics of the vehicle directly. First, a collision cone approach is used to predict any possible collision with the obstacle and, if necessary, to compute an alternate aiming direction for the vehicle. The vehicle guidance strategy then attempts to quickly align the velocity vector of the vehicle along the aiming point within a fraction of the available time-to-go, which ensures quick reaction leading to safety of the vehicle. The PIGC algorithm presented here essentially has two loops in cascade. In the outer loop (i.e the guidance loop), the velocity vector is aligned with the aiming point by correcting the flight path angles, while simultaneously assuring turn coordination. The outer loop essentially generates the commanded body rates for the inner loop while enforcing the angle corrections through dynamic inversion. In the inner loop (i.e the control loop), these body rates are tracked in a fast dynamic inversion loop by generating the necessary control surface deflections. Simulation studies have been carried out with Six-DOF model of a small real fixed wing UAV with and without actuator model in the system. The comparative study clearly show that the proposed PIGC technique is quite effective in avoiding collisions for both single as well as multiple obstacles. Nomenclature SWing planform area, m 2 bWing span, m c Chord length, m dOffset of the thrust line from the CG of the vehicle., m mMass of the UAV, kḡ q Dynamic pressure, Pa g Acceleration due to gravity, m/s 2 V T

Nonlinear Flight Guidance and Control Design for a Loss-of-thrust Aircraft

“…It is the same model used in a reactive obstacle avoidance problem based on partial integrated guidance and control problem by. 22 In this case, the aircraft is initialized at 50m with the airspeed 20m/s. The scenario requires the aircraft to follow a trajectory that leads to the runway.…”

“…The aircraft data are presented in the reference 22 in which the aerodynamic forces and moments are found from curve fittings on wind tunnel data. The aerodynamic forces and moments are expressed as…”

Neuro-Adaptive Augmented Dynamic Inversion Based PIGC Design for Reactive Obstacle Avoidance of UAVs

“…The PIGC framework, 16,17 utilizes the inherent separation existing between the faster and slower dynamics of the Six-DOF model. In this way, it overcomes the disadvantage of both the IGC design 15 and the conventional design.…”

“…A model-predictive control (MPC) based collision avoidance algorithm is proposed, 3 in which a potential field function is incorporated in the cost function to be minimized. 13 On the contrary, present work has been implemented with an innovative partial integrated guidance and control (PIGC) 16,17 technique, which uses the full nonlinear Six-DOF model 18 of a fixed wing airplane without accounting for the decoupling modes. The advantage of using MPC is that state and input constraints are accounted.…”

“…On the contrary, in the conventional design (executes in three loops), 14 the settling time of the response of different loops will not be able to match with the stringent time-to-go window for obstacle avoidance. However, the PIGC framework 16,17 utilizes the inherent separation existing between the faster and slower dynamics of the Six-DOF model. However, the PIGC framework 16,17 utilizes the inherent separation existing between the faster and slower dynamics of the Six-DOF model.…”