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Found 20 papers, 1 papers with code
Edge-Assisted ML-Aided Uncertainty-Aware Vehicle Collision Avoidance at Urban Intersections
Intersection crossing represents one of the most dangerous sections of the road infrastructure and Connected Vehicles (CVs) can serve as a revolutionary solution to the problem.
Hierarchical Fault-Tolerant Coverage Control for an Autonomous Aerial Agent
The second-stage fault-tolerant controller then aims to follow this reference plan, even in the presence of erroneous control inputs caused by non-Gaussian disturbances.
Synergising Human-like Responses and Machine Intelligence for Planning in Disaster Response
In the rapidly changing environments of disaster response, planning and decision-making for autonomous agents involve complex and interdependent choices.
Pandemic infection forecasting through compartmental model and learning-based approaches
Motivated by this, we present a hybrid pandemic infection forecasting methodology that integrates compartmental model and learning-based approaches.
A Study of Data-driven Methods for Adaptive Forecasting of COVID-19 Cases
Severe acute respiratory disease SARS-CoV-2 has had a found impact on public health systems and healthcare emergency response especially with respect to making decisions on the most effective measures to be taken at any given time.
A Multi-task Learning Framework for Drone State Identification and Trajectory Prediction
The rise of unmanned aerial vehicle (UAV) operations, as well as the vulnerability of the UAVs' sensors, has led to the need for proper monitoring systems for detecting any abnormal behavior of the UAV.
Joint Estimation and Control for Multi-Target Passive Monitoring with an Autonomous UAV Agent
This work considers the problem of passively monitoring multiple moving targets with a single unmanned aerial vehicle (UAV) agent equipped with a direction-finding radar.
Integrated Guidance and Gimbal Control for Coverage Planning With Visibility Constraints
This work proposes an integrated guidance and gimbal control coverage path planning (CPP) approach, in which the mobility and gimbal inputs of an autonomous UAV agent are jointly controlled and optimized to achieve full coverage of a given object of interest, according to a specified set of optimality criteria.
Distributed Search Planning in 3-D Environments With a Dynamically Varying Number of Agents
In this work, a novel distributed search-planning framework is proposed, where a dynamically varying team of autonomous agents cooperate in order to search multiple objects of interest in three-dimension (3-D).
Downing a Rogue Drone with a Team of Aerial Radio Signal Jammers
This work proposes a novel distributed control framework in which a team of pursuer agents equipped with a radio jamming device cooperate in order to track and radio-jam a rogue target in 3D space, with the ultimate purpose of disrupting its communication and navigation circuitry.
A Cooperative Multi-Agent Probabilistic Framework for Search and Track Missions
In this work a robust and scalable cooperative multi-agent searching and tracking framework is proposed.
Jointly-Optimized Searching and Tracking with Random Finite Sets
In this paper, we investigate the problem of joint searching and tracking of multiple mobile targets by a group of mobile agents.
Probabilistic Search and Track with Multiple Mobile Agents
In this paper we are interested in the task of searching and tracking multiple moving targets in a bounded surveillance area with a group of autonomous mobile agents.
Decentralized Search and Track with Multiple Autonomous Agents
Based on this, we develop decentralized cooperative look-ahead strategies for efficient searching and tracking of an unknown number of targets inside a bounded surveillance area.
Adaptive Frequency Band Selection for Accurate and Fast Positioning utilizing SOPs
Signals of opportunity (SOPs) are a promising technique that can be used for relative positioning in areas where global navigation satellite system (GNSS) information is unreliable or unavailable.
An Autonomous Drone System with Jamming and Relative Positioning Capabilities
As the number of unauthorized operations of Unmanned Aerial Vehicles (UAVs) is rising, the implementation of a versatile counter-drone system is becoming a necessity.
Scheduling Aerial Vehicles in an Urban Air Mobility Scheme
Highly populated cities face several challenges, one of them being the intense traffic congestion.
Extracting the fundamental diagram from aerial footage
At large, this system behavior is characterized through the fundamental diagram of a road segment, a region or the network.
Extending the Multiple Traveling Salesman Problem for Scheduling a Fleet of Drones Performing Monitoring Missions
This is an extension of the well-known multiple traveling salesman problem.
Relative Positioning of Autonomous Systems using Signals of Opportunity
For reliable operation, next generation autonomous agents will need enhanced situational perception as well as precise navigation capabilities.
