59 accepted papers
In this paper, we combine first-order approximations of hybrid systems (i.e., the so-called saltation matrix) with previous works on parametric sensitivity for continuous systems to propose a general framework for robust trajectory optimization of hybrid systems subject to parametric uncertainties. …
This paper addresses the challenge of allocating heterogeneous resources among multiple agents in a decentralized manner. Our proposed method, Liquid-Graph-Time Clustering-IPPO, builds upon Independent Proximal Policy Optimization (IPPO) by integrating dynamic cluster consensus, a mechanism that all…
This paper considers the problem of coordinating a group of mobile robots for distributedly estimating the parameters of a diffusion model that generates a time-varying spatial field. We assume that each robot can measure the local concentration of a substance continuously released in the environmen…
We present a novel method for optimizing the posture of kinematically redundant torque-controlled robots to improve robustness during impacts. A rigid impact model is used as the basis for a configuration-dependent metric that quantifies the variation between pre- and post-impact velocities. By find…
Achieving robust and reliable control in robotic systems is crucial, especially in presence of model uncertainties. Over the last years the notion of closed-loop sensitivity has emerged as an effective tool for analyzing and quantifying how uncertainties in the model parameters affect the closed-loo…
Accurate trajectory tracking is crucial in aerial robotics. Optimal control methods such as Nonlinear Model Predictive Control (NMPC) are able to track trajectories exploiting the full nonlinear dynamics while respecting constraints. However, the NMPC model-based nature makes it sensitive to mismatc…
This paper addresses the challenge of allocating heterogeneous resources among multiple agents in a decentralized manner. Our proposed method, Liquid-Graph-Time Clustering-IPPO, builds upon Independent Proximal Policy Optimization (IPPO) by integrating dynamic cluster consensus, a mechanism that all
This paper proposes a method to robustify model predictive path integral (MPPI) control by directly taking into account the effects of parameter uncertainty into the controller formulation. Leveraging the recent notion of closed-loop state sensitivity, the proposed MPPI can consider the state sensit
In this letter, we experimentally validate the recent concepts of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">closed-loop state and input sensitivity</i> in the context of robust manipulation control for a robot manipulator. Our objective is to a
Microrobotics implies actuation-related constraints that make safe telemanipulation particularly challenging. We present a haptic shared control system for electromagnetic-based telemanipulation of a pair of microrobots using a constrained optimization framework. Our contributions include: (1) a Qua
Achieving robust robot control requires explicit treatment of model uncertainties. Closed-loop sensitivity has emerged as a powerful tool to analyze how parameter errors map into state and input deviations through so-called “sensitivity tubes”, traditionally built from <italic xmlns:mml="http://www.
Accurate trajectory tracking is crucial in aerial robotics. Optimal control methods such as Nonlinear Model Predictive Control (NMPC) are able to track trajectories exploiting the full nonlinear dynamics while respecting constraints. However, the NMPC model-based nature makes it sensitive to mismatc
In this work, we propose a framework for the distributed implementation of Quadratic Programs-based controllers, building upon and rectifying a significant limitation in a previously presented approach. The proposed framework is primarily motivated by the distributed implementation of Control Barrie…
This letter introduces an end-to-end trajectory planning algorithm tailored for multi-UAV systems that generates collision-free trajectories in environments populated with both static and dynamic obstacles, leveraging point cloud data. Our approach consists of a 2-branch neural network fed with sens
This letter addresses the problem of generating robust and accurate trajectories taking into account uncertainties in the robot dynamic model. Based on the notion of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">closed-loop sensitivity</i>, which q
In this letter, we detail a comprehensive framework for safe and robust planning for robots in presence of model uncertainties. Our framework is based on the recent notion of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">closed-loop state sensitivi
Closed-loop state sensitivity [1], [2] is a recently introduced notion that can be used to quantify deviations of the closed-loop trajectory of a robot/controller pair against variations of uncertain parameters in the robot model. While local optimization techniques are used in [1], [2] to generate…
In this work, we exploit the recent notion of closed-loop state sensitivity to critically compare three typical controllers for a quadrotor UAV with the goal of evaluating the impact of controller choice, gain tuning and shape of the reference trajectory in minimizing the sensitivity of the closed-l…
We present a decentralized connectivity-maintenance algorithm for controlling a group of quadrotor UAVs with limited field of view (FOV) and not sharing a common reference frame for collectively expressing measurements and commands. This is in contrast to the vast majority of previous works on this…
Nowadays ubiquitous robots must be adaptive and easy to use. To this end, dynamical system-based imitation learning plays an important role. In fact, it allows to realize stable and complex robotic tasks without explicitly coding them, thus facilitating the robot use. However, the adaptation capabil…
Energy tanks have gained popularity inside the robotics and control communities over the last years, since they represent a formidable tool to enforce passivity (and, thus, input/output stability) of a controlled robot, possibly interacting with uncertain environments. One weak point of passificatio…
This letter considers the problem of persistently monitoring a set of moving targets using a team of aerial vehicles. Each agent in the network is assumed equipped with a camera with limited range and Field of View (FoV) providing bearing measurements and it implements an Information Consensus Filte
In this research, we aim to answer the question: How to combine Closed-Loop State and Input Sensitivity-based with Observability-aware trajectory planning? These possibly op-posite optimization objectives can be used to improve trajectory control tracking and, at the same time, estimation performanc…
This paper considers a multi-robot team tasked with monitoring an environmental field of interest over long time horizons. The approach is based on a control-theoretic measure of the information collected by the robots, namely a norm of the constructability Gramian. This measure is leveraged in orde…
Neural Style Transfer (NST) refers to a class of algorithms able to manipulate an element, most often images, to adopt the appearance or style of another one. Each element is defined as a combination of Content and Style: the Content can be conceptually defined as the “what” and the Style as the “ho…
In this work we present our results on dynamic visual servoing for the case of moving targets while also exploring the possibility of using such a controller for interaction with the environment. We illustrate the derivation of a feature space impedance controller for tracking a moving object as wel…
Robotic systems are increasingly used to work in dynamic and/or unstructured environments and to operate with a high degree of safety and autonomy. Consequently, they are often equipped with external sensors capable of perceiving the environment (e.g., cameras) and the contacts that may arise (e.g.
This letter presents an adaptive impedance control architecture for robotic teleoperation of contact tasks featuring continuous interaction with the environment. We use Learning from Demonstration (LfD) as a framework to learn variable stiffness control policies. Then, the learnt state-varying stiff
Teams of coordinated robots have been proven useful in several high-impact applications, including urban search and rescue (USAR) and disaster response. In this context, we present a decentralized haptic-enabled connectivity-maintenance control framework for heterogeneous human-robot teams. The prop
In this paper we extend the previously introduced notion of closed-loop state sensitivity by introducing the concept of input sensitivity and by showing how to exploit it in a trajectory optimization framework. This allows to generate an optimal reference trajectory for a robot that minimizes the st…
We propose a novel shared control and active perception framework combining the skills of a human operator in accomplishing complex tasks with the capabilities of a mobile robot in autonomously maximizing the information acquired by the onboard sensors for improving its state estimation. The human o
In this letter, we address the problem of extracting a feasible set of dynamic parameters characterizing the dynamics of a robot manipulator. We start by identifying through an ordinary least squares approach the dynamic coefficients that linearly parametrize the model. From these, we retrieve a set
Robot-assisted cutting is considered an important task in several fields, such as robotic surgery, nuclear decommissioning, waste management, and manufacturing. Despite the complex dexterity requirements of cutting tasks, very simple mechanically-linked master-slave manipulators still dominate many…
This letter focuses on finding robust paths for a robotic system by taking into account the state uncertainty and the probability of collision. We are interested in dealing with intermittent exteroceptive measurements (e.g., collected from vision). We assume that these cues provide reliable measurem
Balancing is a critical feature for a robot interacting with an unstructured environment. The balancing control should account for unknown perturbation forces that might destabilize the robot when performing the intended tasks. In the case of humanoid robots this challenge is higher due to the inher
This letter presents a wearable haptic device for the forearm and its application in robotic teleoperation. The device is able to provide skin stretch, pressure, and vibrotactile stimuli. Two servo motors, housed in a 3D printed lightweight platform, actuate an elastic fabric belt, wrapped around th
We propose novel haptic guidance methods for a dual-arm telerobotic manipulation system, which are able to deal with several different constraints, such as collisions, joint limits, and singularities. We combine the haptic guidance with shared-control algorithms for autonomous orientation control an
The goal of this paper is to increase the estimation performance of an Extended Kalman Filter for a nonlinear differentially flat system by planning trajectories able to maximize the amount of information gathered by onboard sensors in presence of both process and measurement noises. In a previous w…
In this letter, we consider the problem of letting an aerial robot exploiting its contact with the environment in order to enhance its motion possibilities, in a way reminiscent of legged robots exploiting contact forces for locomotion purposes. As a representative and initial case study, we conside
In this paper we propose a novel general method to let a dynamical system fulfil at best a control task when the nominal parameters are not perfectly known. The approach is based on the introduction of the novel concept of closed-loop sensitivity, a quantity that relates parameter variations to devi…
Robotic telemanipulators are already widely used in nuclear decommissioning sites for handling radioactive waste. However, currently employed systems are still extremely primitive, making the handling of these materials prohibitively slow and ineffective. As the estimated cost for the decommissionin…
In this letter, we investigate the online generation of optimal trajectories for target tracking with a quadrotor while satisfying a set of image-based and actuation constraints. We consider a quadrotor equipped with a camera (either down or front-looking) with limited field of view. The aim is to f
Shared control is a key technology for various robotic applications in which a robotic system and a human operator are meant to collaborate efficiently. In order to achieve efficient task execution in shared control, it is essential to predict the desired behavior for a given situation or context in…
Teleoperating a quadrotor equipped with a monocular camera for exploring a wide area in search of something has become a common practice in many application scenarios (e.g. search and rescue). In order to efficiently plan operations, estimating the 3D pose of a point of interest is as important as d…
This paper considers the problem of controlling a formation of quadrotor UAVs equipped with onboard cameras with the goal of maintaining bearing rigidity during motion despite the presence of several sensing constraints, that is, minimum/maximum range, limited camera field of view, and possible occl…
This paper presents image-based navigation from an image memory using a combination of line segments and feature points. The environment is represented by a set of key images, which are acquired during a prior mapping phase that defines the path to be followed during the navigation. The switching of…
This paper addresses the problem of mixed initiative, shared control for master-slave grasping and manipulation. We propose a novel system, in which an autonomous agent assists a human in teleoperating a remote slave arm/gripper, using a haptic master device. Our system is designed to exploit the hu…
This paper deals with the problem of active sensing control for nonlinear differentially flat systems. The objective is to improve the estimation accuracy of an observer by determining the inputs of the system that maximise the amount of information gathered by the outputs over a time horizon. In pa…
In this paper, we address the problem of using a camera with limited field of view for controlling the motion of a quadrotor in aggressive flight regimes. We present a minimum time trajectory planning method that guarantees visibility of the image features while allowing the robot to undertake aggre…
We propose in this paper a new active perception scheme based on Model Predictive Control under constraints for generating a sequence of visual servoing tasks. The proposed control scheme is used to compute the motion of a camera whose task is to successively observe a set of robots for measuring th…
Nowadays, one of the largest environmental challenges that European countries must face consists in dealing with the past half century of nuclear waste. In order to optimize maintenance costs, nuclear waste must be sorted, segregated and stored according to its radiation level. Towards this end, in…
This paper considers the problem of controlling a formation of quadrotor UAVs equipped with onboard cameras able to measure relative bearings in their local body frames w.r.t. neighboring UAVs. The control goal is twofold: (i) steering the agent group towards a formation defined in terms of desired…
Cleaning up the past half century of nuclear waste represents the largest environmental remediation project in the whole Europe. Nuclear waste must be sorted, segregated and stored according to its radiation level in order to optimize maintenance costs. The objective of this work is to develop a sha…
In this paper, we propose a novel decentralized active perception strategy that maximizes the convergence rate in estimating the (unmeasurable) formation scale in the context of bearing-based formation localization for robots evolving in ℝ3 × S1. The proposed algorithm does not assume presence of a…
This letter presents a method for image-based navigation from an image memory using line segments as landmarks. The entire navigation process is based on 2-D image information without using any 3-D information at all. The environment is represented by a set of reference images with overlapping landm
The selection of a suitable set of visual features for an optimal performance of closed-loop visual control or Structure from Motion (SfM) schemes is still an open problem in the visual servoing community. For instance, when considering integral region-based features such as image moments, only heur…
In this paper we experimentally validate and compare three different methods for estimating the 3D parameters of a planar scene from a (possibly time-varying) set of feature points acquired by a moving monocular camera. The first method, based on the classical decomposition of the homography matrix,…
Incremental Structure from Motion (SfM) algorithms require, in general, precise knowledge of the camera linear and angular velocities in the camera frame for estimating the 3D structure of the scene. Since an accurate measurement of the camera own motion may be a non-trivial task in several robotics…
One way to deal with occlusions or loss of tracking of the visual features used for visual servoing tasks is to predict the feature behavior in the image plane when the measurements are missing. Different prediction and correction methods have already been proposed in the literature. The purpose of…