Interesting research on safe navigation by autonomous helicopters in unknown urban environments is presented in this paper. The authors propose and compare two approaches to navigation. The first uses sliding mode boundary following to maintain a predetermined distance to obstacles, and the second uses model predictive control (MPC) to plan short horizon trajectories around detected objects. The authors note that these two control methods seem to provide complementary benefits.
In particular, the authors propose an improvement of the sliding mode control approach in the case where the sensor system provides additional information about the en-route obstacles. They also adjust the robust MPC methodology to deal with an unknown environment. The resulting navigation laws are applicable not only to helicopters, but also to a wide range of vehicles that fit in with the mathematical models employed in this research. Additionally, the MPC approach involves online optimization, which helps to ensure better performance. Based on the comparative research results, the approach based on MPC seems superior and better able to avoid obstacles under most of the circumstances examined.
The navigation approaches were tested using a detailed model of an unmanned helicopter. The SIMULINK simulations combine a linearized rotor aerodynamic model with nonlinear rigid body equations to produce a minimum complexity model, only with the essential dynamics of the helicopter. The authors also provide a detailed and comprehensive comparative analysis of the two proposed control approaches. Both approaches were also tested on the Pioneer P3-DX mobile robot. The authors also tested their approaches in real-world experiments with a wheeled robot to demonstrate their potential for real-time application.
The overall work is very well documented with appropriate lemmas, proofs, theorems, and definitions. The authors plan future work on this subject, including extension of these approaches to cooperative scenarios and real-world tests on autonomous helicopters.
