Section: New Results

Control of single and multiple UAVs

State estimation and flight control of quadrotor UAVs

Participants : Riccardo Spica, Paolo Robuffo Giordano.

Over the last years the robotics community witnessed an increasing interest in the Unmanned Aerial Vehicle (UAV) field. In particular quadrotor UAVs have become more and more widespread in the community as experimental platform for, e.g., testing novel 3D planning, control and estimation schemes in real-world indoor and outdoor conditions. Indeed, in addition to being able to take-off and land vertically, quadrotors can reach high angular accelerations thanks to the relatively long lever arm between opposing motors. This makes them more agile than most standard helicopters or similar rotorcraft UAVs, and thus very suitable to realize complex tasks such as aerial mapping, air pollution monitoring, traffic management, inspection of damaged buildings and dangerous sites, as well as agricultural applications such as pesticide spraying.

Key components for the successful deployment of such systems are (i) a reliable state estimation module able to deal with highly unstructured and/or GPS-denied indoor environments, and (ii) a robust flight control algorithm able to cope with model uncertainties and external disturbances (e.g., adverse atmospheric conditions). The difficulty of these estimation and control problems is also increased by the limited amount of sensing and processing capabilities onboard standard quadrotors: this clearly imposes additional strict requirements on the complexity of the employed algorithms.

In the context of robust flight control of standard quadrotors, the works [31] , [32] addressed the theoretical developments and experimental validation of a novel nonlinear adaptive flight controller able to estimate online the UAV dynamic parameters (such as the position of the center of mass when carrying unmodeled payloads), and to compensate for external wind gusts. In parallel, we also developed in [63] a high performance and open-source hardware/software control architecture for flight control of quadrotor UAVs made available to the general public on a open repository. This was achieved by combining state-of-the-art filtering and control techniques with a careful customization and calibration of a commercially available and low-cost quadrotor platform. Finally, still in the context of flight control, the work [58] reported a successful experimental validation of several flight tests for a novel overactuated quadrotor design with tilting propellers behaving as a fully-actuated rigid body in 3D space (thus, able to control its position and orientation in a fully decoupled way).

As for state estimation, the work [41] introduces a novel nonlinear estimation filter meant to obtain a metric measurement of the body-frame linear velocity from optical flow decomposition (thus, visual input) and concurrent fusion of the accelerometer/gyro readings from the onboard IMU. The peculiarity of this filtering technique is the possibility to both explicitly characterize and impose the transient response of the estimation error (thus, the filter performance) by acting on the estimation gains and UAV motion (acceleration). This is in contrast with the consolidated use of EKF schemes which, because of their inherent linearization of the system dynamics, do not typically allow to draw any conclusions about the stability/transient response of the estimation error.

These works were realized in collaboration with the robotics groups at the University of Cassino, Italy, and at the Max Planck Institute for Biological Cybernetics, Tübingen, Germany.

Collective control of multiple UAVs

Participant : Paolo Robuffo Giordano.

The challenge of coordinating the actions of multiple robots is inspired by the idea that proper coordination of many simple robots can lead to the fulfilment of arbitrarily complex tasks in a robust (to single robot failures) and highly flexible way. Teams of multi-robots can take advantage of their number to perform, for example, complex manipulation and assembly tasks, or to obtain rich spatial awareness by suitably distributing themselves in the environment. Within the scope of robotics, autonomous search and rescue, firefighting, exploration and intervention in dangerous or inaccessible areas are the most promising applications.

In the context of multi-robot (and multi-UAV) coordinated control, connectivity of the underlying graph is perhaps the most fundamental requirement in order to allow a group of robots accomplishing common goals by means of decentralized solutions. In fact, graph connectivity ensures the needed continuity in the data flow among all the robots in the group which, over time, makes it possible to share and distribute the needed information. In this respect, in [23] a fully decentralized strategy for continuous connectivity maintenance for a group of UAVs has been theoretically developed and experimentally validated on a team of 4 quadrotor UAVs. An extension for allowing an external planner (e.g., a human user) to vary online the minimum degree of connectivity of the group was also proposed in [59] . Finally, [48] dealt with the issue of coupling the purely reactive strategy for connectivity maintenance with an autonomous exploration algorithm in a cluttered 3D environment (still experimentally tested on a team of quadrotor UAVs). The complete software architecture developed for performing these and similar multi-UAV experiments was also published in [42] .

These works were realized in collaboration with the robotics group at the Max Planck Institute for Biological Cybernetics, Tübingen, Germany.