Motion primitive based random planning for loco-manipulation tasks

Several advanced control laws are available for complex robotic systems such as humanoid robots and mobile manipulators. Controls are usually developed for locomotion or for manipulation purposes. Resulting motions are usually executed sequentially and the potentiality of the robotic platform is not fully exploited. In this work we consider the problem of loco-manipulation planning for a robot with given parametrized control laws known as primitives. Such primitives, may have not been designed to be executed simultaneously and by composing them instability may easily arise. With the proposed approach, primitives combination that guarantee stability of the system are obtained resulting in complex whole-body behavior. A formal definition of motion primitives is provided and a random sampling approach on a manifold with limited dimension is investigated. Probabilistic completeness and asymptotic optimality are also proved. The proposed approach is tested both on a mobile manipulator and on the humanoid robot Walk-Man, performing loco-manipulation tasks

Motion Planning and Control for Multi Vehicle Autonomous Racing at High Speeds

This paper presents a multi-layer motion planning and control architecture for autonomous racing, capable of avoiding static obstacles, performing active overtakes, and reaching velocities above 75 $m/s$. The used offline global trajectory generation and the online model predictive controller are highly based on optimization and dynamic models of the vehicle, where the tires and camber effects are represented in an extended version of the basic Pacejka Magic Formula. The proposed single-track model is identified and validated using multi-body motorsport libraries which allow simulating the vehicle dynamics properly, especially useful when real experimental data are missing. The fundamental regularization terms and constraints of the controller are tuned to reduce the rate of change of the inputs while assuring an acceptable velocity and path tracking. The motion planning strategy consists of a Fren\'et-Frame-based planner which considers a forecast of the opponent produced by a Kalman filter. The planner chooses the collision-free path and velocity profile to be tracked on a 3 seconds horizon to realize different goals such as following and overtaking. The proposed solution has been applied on a Dallara AV-21 racecar and tested at oval race tracks achieving lateral accelerations up to 25 $m/s^{2}$.Comment: Accepted to the 25th IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2022

Efficient Walking Gait Generation via Principal Component Representation of Optimal Trajectories: Application to a Planar Biped Robot With Elastic Joints

Recently, the method of choice to exploit robot dynamics for efficient walking is numerical optimization (NO). The main drawback in NO is the computational complexity, which strongly affects the time demand of the solution. Several strategies can be used to make the optimization more treatable and to efficiently describe the solution set. In this letter, we present an algorithm to encode effective walking references, generated offline via numerical optimization, extracting a limited number of principal components and using them as a basis of optimal motions. By combining these components, a good approximation of the optimal gaits can be generated at run time. The advantages of the presented approach are discussed, and an extensive experimental validation is carried out on a planar legged robot with elastic joints. The biped thus controlled is able to start and stop walking on a treadmill, and to control its speed dynamically as the treadmill speed change

Optimal control to reduce emissions in gasoline engines: An iterative learning control approach for ECU calibration maps improvement

Control of emissions in gasoline engines has become more stringent in the last decades, especially in Europe, posing new and important problems in the control of complex nonlinear systems. In this work a preliminary investigation is conducted on the idea of exploiting Iterative Learning Control to optimize calibration maps that are commonly used in the Engine Control Unit of gasoline engines. In this spirit, starting from existing maps, we show how to refine them using a gradient-descent iterative learning control algorithm, considering additional constraints in the optimization problem. The outcome of this procedure is a control signal which can be integrated in a modified map. The performance of the proposed technique is validated on the provided training signal and cross-validated on different reference signals. Simulation results show the effectiveness of the approach

LHF Connect: a DIY telepresence robot against COVID-19

This contribution describes a case study of a “do-it-yourself” (DIY) opensource service and related product to help combating the COVID-19 emergency. It illustrates the birth of LHF Connect, a project designed to facilitate communication between patients isolated in COVID-19 hospitals’ ward and their relatives. LHF Connect is a teleoperated robot that can move in autonomy around the hospital. A User Centered Design approach, methods and specific tools helped in managing crucial steps of the design process such as i) the collection of needs coming from the context, stakeholders and end-users; ii) defining the service blueprint; iii) imagining finishing concepts; and iv) managing the communication activities. The initiative has been promoted by a multidisciplinary team of researchers (mainly roboticists with the help of specific competences coming from Design discipline)

er.autopilot 1.0: The Full Autonomous Stack for Oval Racing at High Speeds

The Indy Autonomous Challenge (IAC) brought together for the first time in history nine autonomous racing teams competing at unprecedented speed and in head-to-head scenario, using independently developed software on open-wheel racecars. This paper presents the complete software architecture used by team TII EuroRacing (TII-ER), covering all the modules needed to avoid static obstacles, perform active overtakes and reach speeds above 75 m/s (270 km/h). In addition to the most common modules related to perception, planning, and control, we discuss the approaches used for vehicle dynamics modelling, simulation, telemetry, and safety. Overall results and the performance of each module are described, as well as the lessons learned during the first two events of the competition on oval tracks, where the team placed respectively second and third.Comment: Preprint: Accepted to Field Robotics "Opportunities and Challenges with Autonomous Racing" Special Issu

Automatica. RAccolta di esercizi risolti (con appendice Matlab)

Questo libro presenta una raccolta di esercizi risolti per la preparazione all'esame di Fondamenti di Automatica o di corsi analoghi di base su questi argomenti. Il contenuto del libro deriva dall'attività didattica che gli autori svolgono da parecchi anni nell'ambito del corso di Fondamenti di Automatica per la Laurea in Ingegneria Gestionale presso il Politecnico di Milano e rispecchia pertanto il programma e gli argomenti sviluppati in tale corso e non intende coprire tutti gli aspetti delle discipline coinvolte. I diversi argomenti sono organizzati in capitoli secondo un filo logico che va dalle basi della teoria dei sistemi all'analisi nel tempo e in frequenza di sistemi di controllo in retroazione. L'obiettivo di questo testo è quello di essere un utile supporto nello studio di una materia che inizialmente può apparire complessa ed eccessivamente teorica ma che, una volta approfondita, può invece portare ad una nuova mentalità ingegneristica, sia nello studio che nella professione. L'Automatica rappresenta non a caso una delle materie trasversali di numerosi corsi di laurea dell'area dell'Ingegneria Industriale e dell'Informazione

Adaptive nonlinear control of braking in railway vehicles

In this work a new technique for anti-slip control in railway vehicles is proposed. This technique is based on a new parametrization of the adherence unknown force. The control philosophy is alternative to the ones currently implemented in the industry and found in the literature, and aims at enhancing vehicle performances by estimating the maximum available adhesion force, which is then exploited via a nonlinear controller. The effects of the implemented control scheme are the use of the maximum available deceleration in case of poor adhesion conditions and, consequently, a reduction in the wear rate of the rolling stock. The results are illustrated via simulation