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Found 9 papers, 1 papers with code
Cooperative Sense and Avoid for UAVs using Secondary Radar
A cooperative Sense and Avoid (SAA) algorithm for safe navigation of small-sized UAVs within an airspace is proposed in this paper.
On the choice of reference in offset calibration
If the underlying noise is homoscedastic in nature, then we prove the \emph{average} reference yields a factor $2$ improvement on the variance, as compared to any arbitrarily chosen reference within the network.
Artificial Potential Field-Based Path Planning for Cluttered Environments
First, we propose to improve an existing classical method that replaces the gradient descent optimization of the potential field cost function on a continuous domain with a combinatorial optimization on a set of predefined points (called bacteria points) around the agent's current location.
Multi-FEAT: Multi-Feature Edge AlignmenT for Targetless Camera-LiDAR Calibration
The accurate environment perception of automobiles and UAVs (Unmanned Ariel Vehicles) relies on the precision of onboard sensors, which require reliable in-field calibration.
Joint Ranging and Phase Offset Estimation for Multiple Drones using ADS-B Signatures
While the proposed estimator can estimate the range of multiple drones with a single receive antenna, a larger number of drones can be supported with higher accuracy by the use of multiple antennas at the receiver.
Performance Bounds for Cooperative Localisation in the Starlink Network
To this end, we study the performance of any unbiased estimator for localisation, by calculating the instantaneous Cram$\acute{\text{e}}$r-Rao bound for two situations; one in which inter-satellite measurements and measurements from ground stations were considered, and one in which only relative navigation from inter-satellite measurements were considered.
Relative Kinematics Estimation Using Accelerometer Measurements
In this paper, we propose a time-varying Grammian-based data model for estimating the relative kinematics of mobile nodes with polynomial trajectories, given the time-varying pairwise distance measurements between the nodes.
Distributed Kalman Filters for Relative Formation Control of Mobile Agents
Formation control (FC) of multi-agent plays a critical role in a wide variety of fields.
Unsupervised Heart-rate Estimation in Wearables With Liquid States and A Probabilistic Readout
The novelty of our approach lies in (1) encoding spatio-temporal properties of ECG signals directly into spike train and using this to excite recurrently connected spiking neurons in a Liquid State Machine computation model; (2) a novel learning algorithm; and (3) an intelligently designed unsupervised readout based on Fuzzy c-Means clustering of spike responses from a subset of neurons (Liquid states), selected using particle swarm optimization.
