Angel Santamaria-Navarro

Hybrid visual servoing with hierarchical task composition for aerial manipulation

In this letter, a hybrid visual servoing with a hierarchical task-composition control framework is described for aerial manipulation, i.e., for the control of an aerial vehicle endowed with a robot arm. The proposed approach suitably combines into a unique hybrid-control framework the main benefits of both image-based and position-based control schemes. Moreover, the underactuation of the aerial vehicle has been explicitly taken into account in a general formulation, together with a dynamic smooth activation mechanism. Both simulation case studies and experiments are presented to demonstrate the performance of the proposed technique.

Task priority control for aerial manipulation

This paper presents a task oriented control strategy for aerial vehicles equipped with a manipulator. A camera is attached to the end-effector of the manipulator to perform a primary task consisting on visual servoing towards a desired target. Over-actuation of the whole quadrotor-arm system is exploited to achieve secondary velocity tasks. One subtask is proposed to horizontally stabilize the platform during flight by aligning the arm center of gravity with the quadrotor gravitational vector. The arm singularities and manipulability are addressed by another subtask that leads the arm to a preferable configuration, and also takes into account the arm joint limits. The performance of the whole visual servo and secondary tasks control scheme is shown in a Robot Operating System (ROS) implementation.

Uncalibrated Visual Servo for Unmanned Aerial Manipulation

This paper addresses the problem of autonomous servoing an unmanned redundant aerial manipulator using computer vision. The overactuation of the system is exploited by means of a hierarchical control law, which allows to prioritize several tasks during flight. We propose a safety-related primary task to avoid possible collisions. As a secondary task, we present an uncalibrated image-based visual servo strategy to drive the arm end-effector to a desired position and orientation by using a camera attached to it. In contrast to the previous visual servo approaches, a known value of camera focal length is not strictly required. To further improve flight behavior, we hierarchically add one task to reduce dynamic effects by vertically aligning the arm center of gravity to the multirotor gravitational vector, and another one that keeps the arm close to a desired configuration of high manipulability and avoiding arm joint limits. The performance of the hierarchical control law, with and without activation of each of the tasks, is shown in simulations and in real experiments confirming the viability of such prioritized control scheme for aerial manipulation.

Trajectory Generation for Unmanned Aerial Manipulators Through Quadratic Programming

In this paper, a trajectory generation approach using quadratic programming is described for aerial manipulation, i.e., for the control of an aerial vehicle equipped with a robot arm. The proposed approach applies the online active set strategy to generate a feasible trajectory of the joints, in order to accomplish a set of tasks with defined bounds and constraint inequalities. The definition of the problem in the acceleration domain allows to integrate and perform a large set of tasks and, as a result, to obtain smooth motion of the joints. A weighting strategy, associated with a normalization procedure, allows us to easily define the relative importance of the tasks. This approach is useful to accomplish different phases of a mission with different redundancy resolution strategies. The performance of the proposed technique is demonstrated through real experiments with all the algorithms running onboard in real time. In particular, the aerial manipulator can successfully perform navigation and interaction phases, while keeping motion within prescribed bounds and avoiding collisions with external obstacles.

High-frequency MAV state estimation using low-cost inertial and optical flow measurement units

This paper develops a simple and low-cost method for 3D, high-rate vehicle state estimation, specially designed for free-flying Micro Aerial Vehicles (MAVs). We fuse observations from inertial measurement units and the recently appeared low-cost optical flow smart cameras. These smart cameras integrate a sonar altimeter, a triaxial gyrometer and an optical flow sensor, and directly provide metric ego-motion information in the form of body velocities and altitude. Compared to state-of-the-art visual-inertial odometry methods, we are able to drastically reduce the computational load in the main processor unit, and obtain an accurate estimation of the vehicle state at a high update rate of 100Hz. We thus extend the current use of these smart cameras from hovering purposes to odometry estimation. In order to propose a simple algorithmic solution, we investigate the performances of two Kalman filters, in the extended and error-state flavors, alongside a large number of algorithm variations, using simulations and real experiments with precise ground-truth. We observe that the marginal performance gain attained with these algorithm improvements does not pay for the effort of implementing them. We conclude that a classical EKF in its simplest form is sufficient for providing motion estimates that coherently exploit the available measurements.

Nonlinear model predictive control for aerial manipulation

This paper presents a nonlinear model predictive controller to follow desired 3D trajectories with the end effector of an unmanned aerial manipulator (i.e., a multirotor with a serial arm attached). To the knowledge of the authors, this is the first time that such controller runs online and on board a limited computational unit to drive a kinematically augmented aerial vehicle. Besides the trajectory following target, we explore the possibility of accomplishing other tasks during flight by taking advantage of the system redundancy. We define several tasks designed for aerial manipulators and show in simulation case studies how they can be achieved by either a weighting strategy, within a main optimization process, or a hierarchical approach consisting on nested optimizations. Moreover, experiments are presented to demonstrate the performance of such controller in a real robot.

A flexible hardware-in-the-loop architecture for UAVs

As robotic technology matures, fully autonomous robots become a realistic possibility, but demand very complex solutions to be rapidly engineered. In order to be able to quickly set up a working autonomous system, and to reduce the gap between simulated and real experiments, we propose a modular, upgradeable and flexible hardware-in-the- loop (HIL) architecture, which hybridizes the simulated and real settings. We take as use case the autonomous exploration of dense forests with UAVs, with the aim of creating useful maps for forest inspection, cataloging, or to compute other metrics such as total wood volume. As the first step in the development of the full system, in this paper we implement a fraction of this architecture, comprising assisted localization, and automatic methods for mapping, planning and motion execution. Specifically we are able to simulate the use of a 3D LIDAR endowed below an actual UAV autonomously navigating among simulated obstacles, thus the platform safety is not compromised. The full system is modular and takes profit of pieces either publicly available or easily programmed. We highlight the flexibility of the proposed HIL architecture to rapidly configure different experimental setups with a UAV in challenging terrain. Moreover, it can be extended to other robotic fields without further design. The HIL system uses the multi-platform ROS capabilities and only needs a motion capture system as external extra hardware, which is becoming standard equipment in all research labs dealing with mobile robots.

Robot State Estimation

Micro aerial vehicles have gained significant attention in the last decade both in academia and industry, mostly due to their potential use in a wide range of applications such as exploration [46], inspection [52], mapping, interaction with the environment [7, 44], search and rescue [27], and to their significant mechanical simplicity and ease of control. Moreover, their ability to operate in confined spaces, hover in space and even perch, together with a decrease in cost make them very attractive with tremendous potential as UAM flying platforms.

Visual guidance of unmanned aerial manipulators

A thesis submitted to the Universitat Politecnica de Catalunya for the degree of Doctor of Philosophy. Doctoral Programme: Automatic Control, Robotics and Computer Vision. This thesis has been completed at: Institut de Robotica i Informatica Industrial, CSIC-UPC.

The AEROARMS Project: Aerial Robots with Advanced Manipulation Capabilities for Inspection and Maintenance

This article summarizes new aerial robotic manipulation technologies and methods-aerial robotic manipulators with dual arms and multidirectional thrusters-developed in the AEROARMS project for outdoor industrial inspection and maintenance (I&M).