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Found 18 papers, 1 papers with code
An Active-Sensing Approach for Bearing-based Target Localization
Characterized by a cross-disciplinary nature, the bearing-based target localization task involves estimating the position of an entity of interest by a group of agents capable of collecting noisy bearing measurements.
Trajectory Tracking for Tilted Hexarotors with Concurrent Attitude Regulation
Tilted hexarotors embody a technology that remains partially unexploited in terms of its potential, especially concerning precise and concurrent position and attitude control.
A Natural Indirect Adaptive Controller for a Satellite-Mounted Manipulator
The work considers the design of an indirect adaptive controller for a satellite equipped with a robotic arm manipulating an object.
Adaptive Consensus-based Reference Generation for the Regulation of Open-Channel Networks
This paper deals with water management over open-channel networks (OCNs) subject to water height imbalance.
Optimal Time-Invariant Distributed Formation Tracking for Second-Order Multi-Agent Systems
This paper addresses the optimal time-invariant formation tracking problem with the aim of providing a distributed solution for multi-agent systems with second-order integrator dynamics.
Quaternion-based non-singular terminal sliding mode control for a satellite-mounted space manipulator
In this paper, a robust control solution for a satellite equipped with a robotic manipulator is presented.
Distributed Dual Quaternion Based Localization of Visual Sensor Networks
In this paper we consider the localization problem for a visual sensor network.
On the Distributed Estimation from Relative Measurements: a Graph-Based Convergence Analysis
For a multi-agent system state estimation resting upon noisy measurements constitutes a problem related to several application scenarios.
Optimal Time-Invariant Formation Tracking for a Second-Order Multi-Agent System
Given a multi-agent linear system, we formalize and solve a trajectory optimization problem that encapsulates trajectory tracking, distance-based formation control and input energy minimization.
Distributed Strategies for Dynamic Coverage with Limited Sensing Capabilities
In this work, it is presented the development of a novel distributed algorithm performing robotic coverage, clustering and dispatch around an event in static-obstacle structured environments without relying on metric information.
Visual Sensor Network Stimulation Model Identification via Gaussian Mixture Model and Deep Embedded Features
Visual sensor networks (VSNs) constitute a fundamental class of distributed sensing systems, with unique complexity and appealing performance features, which correspondingly bring in quite active lines of research.
Nonlinear modeling and feedback control of boom barrier automation
We address modeling and control of a gate access automation system.
A General Regularized Distributed Solution for System State Estimation from Relative Measurements
This work presents a novel general regularized distributed solution for the state estimation problem in networked systems.
Online and Adaptive Parking Availability Mapping: An Uncertainty-Aware Active Sensing Approach for Connected Vehicles
Research on connected vehicles represents a continuously evolving technological domain, fostered by the emerging Internet of Things (IoT) paradigm and the recent advances in intelligent transportation systems.
Transmitter Discovery through Radio-Visual Probabilistic Active Sensing
Multi-modal Probabilistic Active Sensing (MMPAS) uses sensor fusion and probabilistic models to control the perception process of robotic sensing platforms.
A Proximal Point Approach for Distributed System State Estimation
System state estimation constitutes a key problem in several applications involving multi-agent system architectures.
Probabilistic RF-Assisted Camera Wake-Up through Self-Supervised Gaussian Process Regression
In this paper we consider a wireless smart camera, equipped with a low-energy radio receiver, and used to visually detect a moving radio-emitting target.
Learning to falsify automated driving vehicles with prior knowledge
While automated driving technology has achieved a tremendous progress, the scalable and rigorous testing and verification of safe automated and autonomous driving vehicles remain challenging.
