9 papers
Enhancing Multi-Robot Exploration Using Probabilistic Frontier Prioritization with Dirichlet Process Gaussian Mixtures
John Lewis Devassy, Meysam Basiri, Mário A. T. Figueiredo +1
Multi-agent autonomous exploration is essential for applications such as environmental monitoring, search and rescue, and industrial-scale surveillance. However, effective coordina…
Asymptotically-Bounded 3D Frontier Exploration enhanced with Bayesian Information Gain
John Lewis, Meysam Basiri, Pedro U. Lima
Robotic exploration in large-scale environments is computationally demanding due to the high overhead of processing extensive frontiers. This article presents an OctoMap-based fron…
Lightweight 3D LiDAR-Based UAV Tracking: An Adaptive Extended Kalman Filtering Approach
Nivand Khosravi, Meysam Basiri, Rodrigo Ventura
Accurate relative positioning is crucial for swarm aerial robotics, enabling coordinated flight and collision avoidance. Although vision-based tracking has been extensively studied…
Unsupervised LiDAR-Based Multi-UAV Detection and Tracking Under Extreme Sparsity
Nivand Khosravi, Rodrigo Ventura, Meysam Basiri
Non-repetitive solid-state LiDAR scanning leads to an extremely sparse measurement regime for detecting airborne UAVs: a small quadrotor at 10-25 m typically produces only 1-2 retu…
Robust Cooperative Localization in Featureless Environments: A Comparative Study of DCL, StCL, CCL, CI, and Standard-CL
Nivand Khosravi, Rodrigo Ventura, Meysam Basiri
Cooperative localization (CL) enables accurate position estimation in multi-robot systems operating in GPS-denied environments. This paper presents a comparative study of five CL a…
Distributed Kalman--Consensus Filtering with Adaptive Uncertainty Weighting for Multi-Object Tracking in Mobile Robot Networks
Niusha Khosravi, Rodrigo Ventura, Meysam Basiri
This paper presents an implementation and evaluation of a Distributed Kalman--Consensus Filter (DKCF) for Multi-Object Tracking (MOT) in mobile robot networks operating under parti…