Showing papers by "Marco Tognon published in 2020"

Direct Force Feedback Control and Online Multi-Task Optimization for Aerial Manipulators

Abstract: In this letter we present an optimization-based method for controlling aerial manipulators in physical contact with the environment. The multi-task control problem, which includes hybrid force-motion tasks, energetic tasks, and position/postural tasks, is recast as a quadratic programming problem with equality and inequality constraints, which is solved online. Thanks to this method, the aerial platform can be exploited at its best to perform the multi-objective tasks, with tunable priorities, while hard constraints such as contact maintenance, friction cones, joint limits, maximum and minimum propeller speeds are all respected. An on-board force/torque sensor mounted at the end effector is used in the feedback loop in order to cope with model inaccuracies and reject external disturbances. Real experiments with a multi-rotor platform and a multi-DoF lightweight manipulator demonstrate the applicability and effectiveness of the proposed approach in the real world.

Full-Pose Manipulation Control of a Cable-Suspended Load With Multiple UAVs Under Uncertainties

Abstract: In this work we propose an uncertainty-aware controller for the Fly-crane system, a statically rigid cable-suspended aerial manipulator using the minimum number of aerial robots and cables. The force closure property of the Fly-crane makes it ideal for applications where high precision is required and external disturbances should be compensated. The proposed control requires the knowledge of the nominal values of a minimum number of uncertain kinematic parameters, thus simplifying the identification process and the controller implementation. We propose an optimization-based tuning method of the control gains that ensures stability despite parameter uncertainty and maximizes the $H_\infty$ performance. The validity of the proposed framework is shown through real experiments.

Physical Human-Robot Interaction with a Tethered Aerial Vehicle: Application to a Force-based Human Guiding Problem

Abstract: Today, physical Human-Robot Interaction (pHRI) is a very popular topic in the field of ground manipulation. At the same time, Aerial Physical Interaction (APhI) is also developing very fast. Nevertheless, pHRI with aerial vehicles has not been addressed so far. In this work, we present the study of one of the first systems in which a human is physically connected to an aerial vehicle by a cable. We want the robot to be able to pull the human toward a desired position (or along a path) only using forces as an indirect communication-channel. We propose an admittance-based approach that makes pHRI safe. A controller, inspired by the literature on flexible manipulators, computes the desired interaction forces that properly guide the human. The stability of the system is formally proved with a Lyapunov-based argument. The system is also shown to be passive, and thus robust to non-idealities like additional human forces, time-varying inputs, and other external disturbances. We also design a maneuver regulation policy to simplify the path following problem. The global method has been experimentally validated on a group of four subjects, showing a reliable and safe pHRI.

Theory and Applications for Control of Aerial Robots in Physical Interaction Through Tethers

Abstract: This book studies how autonomous aerial robots physically interact with the surrounding environment. Intended to promote the advancement of aerial physical interaction, it analyzes a particular class of aerial robots: tethered aerial vehicles. By examining specific systems, while still considering the challenges of the general problem, it will help readers acquire the knowledge and expertise needed for the subsequent development of more general methods applicable to aerial physical interaction. The formal analysis covers topics ranging from control, state estimation, and motion planning, to experimental validation. Addressing both theoretical and technical aspects, the book is intended for a broad academic and industrial readership, including undergraduate students, researchers and engineers. It can be used as a teaching reference, or as the basis for product development.

Survey on Aerial Multirotor Design: a Taxonomy Based on Input Allocation

Abstract: This paper reviews the impact of multirotor aerial vehicles designs on their abilities in terms of tasks and system properties. We propose a general taxonomy to characterize and describe multirotor aerial vehicles and their design, which we apply exhaustively on the vast literature available. Thanks to the systematic characterization of the designs we exhibit groups of designs having the same abilities in terms of achievable tasks and system properties. In particular, we organize the literature review based on the number of atomic actuation units and we discuss global properties arising from their choice and spatial distribution in the designs. Finally, we provide a discussion on the common traits of the designs found in the literature and the main future open problems.

A study on force-based collaboration in swarms

Abstract: Cooperative manipulation is a basic skill in groups of humans, animals and in many robotic applications. Besides being an interesting challenge, communication-less approaches have been applied to groups of robots in order to achieve higher scalability and simpler hardware and software design. We present a generic model and control law for robots cooperatively manipulating an object, for both ground and floating systems. The control method exploits a leader–follower scheme and is based only on implicit communication (i.e., the sensing of contact forces). The control objective mainly consists of steering the object manipulated by the swarm of robots to a desired position and orientation in a cooperative way. For a system with just one leader, we present analytical results on the equilibrium configurations and their stability that are then validated by numerical simulations. The role of object internal forces (induced by the robots through contact forces) is discussed in terms of convergence of the object position and orientation to the desired values. We also present a discussion on additional properties of the controlled system that were investigated using thorough numerical analysis, namely the robustness of the system when the object is subject to external disturbances in non-ideal conditions, and how the number of leaders in the swarm can affect the aforementioned convergence and robustness.

Cooperative Aerial Load Transportation via Sampled Communication

Abstract: In this work, we propose a feedback-based motion planner for a class of multi-agent manipulation systems with a sparse kinematics structure. In other words, the agents are coupled together only by the transported object. The goal is to steer the load into a desired configuration. We suppose that a global motion planner generates a sequence of desired configurations that satisfy constraints as obstacles and singularities avoidance. Then, a local planner receives these references and generates the desired agents velocities, which are converted into force inputs for the vehicles. We focus on the local planner design both in the case of continuously available measurements and when they are transmitted to the agents via sampled communication. For the latter problem, we propose two strategies. The first is the discretization of the continuous-time strategy that preserves stability and guarantees exponential convergence regardless of the sampling period. In this case, the planner gain is static and computed off-line. The second strategy requires to collect the measurements from all sensors and to solve online a set of differential equations at each sampling period. However, it has the advantage to provide doubly exponential convergence. Numerical simulations of these strategies are provided for the cooperative aerial manipulation of a cable-suspended load.

Omni-Plus-Seven (O7+): An Omnidirectional Aerial Prototype with a Minimal Number of Unidirectional Thrusters

Abstract: The aim of this paper is to present the design of a novel omnidirectional Unmanned Aerial Vehicle (UAV) with seven unidirectional thrusters, called $O_ + ^7$. The paper formally defines the O + design for a generic number of propellers and presents its necessary conditions; then it illustrates a method to optimize the placement and orientation of the platform’s propellers to achieve a balanced O + design. The paper then details the choice of the parameters of the $O_ + ^7$ UAV, and highlights the required mechanical and electrical components. The resultant platform is tested in simulation, before being implemented as a prototype. The prototype is firstly static-bench tested to match its nominal and physical models, followed by hovering tests in multiple orientations. The presented prototype shows the ability to fly horizontally, upside down and at a tilted angle.

Direct Acceleration Feedback Control of Quadrotor Aerial Vehicles

Abstract: In this paper we propose to control a quadrotor through direct acceleration feedback. The proposed method, while simple in form, alleviates the need for accurate estimation of platform parameters such as mass and propeller effectiveness. In order to use efficaciously the noisy acceleration measurements in direct feedback, we propose a novel regression-based filter that exploits the knowledge on the commanded propeller speeds, and extracts smooth platform acceleration with minimal delay. Our tests show that the controller exhibits a few millimeter error when performing real world tasks with fast changing mass and effectiveness, e.g., in pick and place operation and in turbulent conditions. Finally, we benchmark the direct acceleration controller against the PID strategy and show the clear advantage of using high-frequency and low-latency acceleration measurements directly in the control feedback, especially in the case of low frequency position measurements that are typical for real outdoor conditions.

Inertial Estimation and Energy-Efficient Control of a Cable-suspended Load with a Team of UAVs

Abstract: The Fly-Crane is a multi-robot aerial manipulator system composed of three aerial vehicles towed to a platform by means of six cables. This paper presents a method to estimate the mass and the position of the center of mass of a loaded platform (i.e. the Fly-Crane platform including a transported load). The precise knowledge of these parameters allows to sensibly minimize the total effort exerted during a full-pose manipulation task The estimation is based on the measure of the forces applied by the aerial vehicles to the platform in different static configurations. We demonstrate that only two different configurations are sufficient to estimate the inertial parameters. Far-from-ideal numerical simulations show the effectiveness of the estimation method. Once the parameters are estimated, we show the enhancement of the system performances by minimizing the total exerted effort. The validity of the proposed algorithm in non-ideal conditions is presented through simulations based on the Gazebo simulator.

Communication-based and Communication-less approaches for Robust Cooperative Planning in Construction with a Team of UAVs

Abstract: In this paper, we analyze the coordination problem of groups of aerial robots for assembly applications. With the enhancement of aerial physical interaction, construction applications are becoming more and more popular. In this domain, the multi-robot solution is very interesting to reduce the execution time. However, new methods to coordinate teams of aerial robots for the construction of complex structures are required. In this work, we propose an assembly planner that considers both assembly and geometric constraints imposed by the particular desired structure and employed robots, respectively. An efficient graph representation of the task dependencies is employed. Based on this framework, we design two assembly planning algorithms that are robust to robot failures. The first is centralized and communication-based. The second is distributed and communication-less. The latter is a solution for scenarios in which the communication network is not reliable. Both methods are validated by numerical simulations based on the assembly scenario of Challenge 2 of the robotic competition MBZIRC2020.