Chapter VI: General Conclusions and Future Work

6.1. Review

The main goal achieved during the development of this thesis is definitively the design and implementation of the entire MAV indoor/outdoor navigation (M-ION) architecture. This implementation process regarded all the necessary steps in order to achieve a level of autonomy that only involves the user in case of supervision. Those steps are:

๏ Understanding the behavior of a complex underactuated system, such as the quadrotor and the coaxial mechanism, requires the analysis and development of complex dynamics equations of motion, essentially for the modeling and control purposes.

๏ Implementing robust control algorithms (based on the non-linear models) that provide system reliability for carrying out autonomous flying tasks.

๏ Achieving the desired level of autonomy during MAV navigation.

Fig. 6.1 The M-ION architecture put into practice: MAV autonomous navigation is being the result.

6.1.1. MAV Modeling

In terms of MAV modeling, the objective was to find a set of Equation of Motion-EOM that described the vehicle dynamics in the 6-dimensional space. The advantages of the use of the spatial algebra in that regard was a success. Variable-compactness and insight of the physical behaviors that rule the MAV dynamics: Gyroscopic forces, Coriolis accelerations, etc allowed to develop a robust dynamics model that subsequently was validated though an identification process. The results of that validation showed how well: friction forces due to aerodynamics, motor dynamics, propeller rolling moments, etc responded during real MAV flight.

6.1.2. MAV control and autonomous navigation

A backstepping+FST methodology has been proposed for attitude control. For full indoor navigation, future work includes addressing vision capability to the DraganFlyer, and finally testing position and altitude control beyond simulation. Nonetheless, results obtained are motivating. At high speed maneuvering (1m/s), the backstepping+FST’s performance (in relation to error tracking) is about 2.5x times better than using PID technique. The PID delays to reject the disturbance whereas the Backstepping+FST “immediately” compensates angular position based on velocity change rate, which consequently improves on the tracking error (in X-Y position). This improvement was basically achieved by introducing a desired angular acceleration command (as a function of the maneuvering velocity) that quickly responds to abrupt angular rate change (more energetic control law, bounded by the acceleration limits), making the attitude stabilization more reliable.

Finally, the fusion of this control approach with the modeling stage and sensor/communication modules allowed the development of the M-ION architecture. Simulation and experimental results confirmed M-ION architecture was suitable for achieving high performance during MAV autonomous navigation tasks.

6.2. Future Work

The development of novel control strategies and methodologies for improving the level of autonomy of miniature flying vehicles remains under current research.

Autonomous flight in confined or cluttered scenarios (e.g. inside buildings) requires strong maneuverability capabilities, fast mapping from sensors to actuators and robust control onboard in order to achieve real-time operation. Current Flying Vehicles tend to fly in open sky (outdoor navigation) far from any obstacles and rely on external beacons -mainly GPS- to being able of auto- localize and perform fully position control. Most of the control architectures and methodologies developed for those kind of systems are strictly dependent from GPS and robust sensors onboard. Evolving to the area of Miniature Flying Vehicles -MFV which main goal is to navigate within indoor and cluttered environments, the previous approaches from perception and control do not work as desired. In this thesis, the problem of indoor and outdoor navigation applied to miniature aerial vehicles was studied, however many things can be improved. Next remarks show some of them.

About the thesis’s topics:

๏ Indoor navigation was only tested under simulation. In order to experiment with indoor tracking tasks based on vision sensing, the current quadrotor’s platforms must be hardware modified in order to address the required vision an communication capacity.

๏ Besides indoor tracking tasks, vision can be used to achieve full autonomous navigation including obstacle avoidance capacity. In this sense, the future work regarding indoor navigation is oriented towards obstacle avoidance based on optic flow control. More complex solutions to achieve a more level of autonomy could be oriented to the development of a SLAM solution that allows the vehicle to -know- about the explored environment. This kind of solutions could provide the foundations to include more “intelligent” cognitive controllers for navigation decision-making and so on.

๏ In terms of outdoor navigation, the inclusion of the previous remarks could be suitable for achieving an even more level of autonomy within the M-ION architecture: obstacle avoidance capacity.

๏ From a control perspective, the introduced backstepping+FST methodology proved to be suitable and reliable for MAV control. Future work is focused on embedding control algorithms onboard the MAVs. In this thesis, the entire M-ION architecture was

implemented off-board the vehicles. This constraints the mission area due to communication links, addresses communication delays, etc. Full autonomous MAVs must include onboard control and navigation methods.

About the Micro Aerial Vehicle topic:

As mentioned at the beginning of this thesis, scientist that research about Micro Aerial Vehicles focus on different aspects depending on the morphology and size of the system (see Fig. 1.1 in Section 1). The aims of future work on MAVs focus on even smaller and with a biological inspired morphology design and behavior.

Future work in this area (currently under analysis) could be oriented towards the development of a so-called: The MicroBat, a bio-inspired morphing-wing flapping Micro Aerial Vehicle. The objective is to build a Bat-robot that uses bio-inspired behavior for locomotion.

The first main goal is to build a bio-inspired BAT Micro-Aerial Vehicle that probably could be use smart materials (e.g. SMA) fibers as the bones/fingers skeleton of the wings. The aim is to achieve the! morphing-wing capability (controlling the SMAs) with the purpose of studying flight aerodynamics. To achieve this, a complete analysis of bat flight will provide the bio-inspired foundations to be used within an artificial counterpart.

6.3. Publications in relation to this thesis-work

Book Chapters:

๏ Barrientos, A., Gutierrez, P., and Colorado, J.D. 2008. Advanced UAV Trajectory Generation:

Planning and Guidance, in book, Aerial Vehicles, published in November by In-Tech, Vol. 1, chapter 4, pp. 55-82, ISBN: 978-953-7619-41-1.

International Conference Proceedings

๏ Colorado, J.D., and Barrientos, A. 2009. Miniature Quad-rotor Dynamics Modeling &

Guidance for Vision- based Target Tracking Control Tasks. Proceedings of The 14th International Conference on Advanced Robotics -ICAR’10, June 22-26, Munich, Germany.! ISBN: 978-1-4244-4855-5

๏ Colorado, J.D, Barrientos, A., and Gutierrez, P. 2009. TG2M: Trajectory Generator and

Guidance Module for the Aerial Vehicle Control Language AVCL. Proceedings of the 40th International Symposium on Robotics- ISR’09, Barcelona-Spain, March. ISBN: 978-84-920933-8-0.

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