Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Van Nguyen Hoa"'
Path planning for autonomous search and tracking of multiple objects is a critical problem in applications such as reconnaissance, surveillance, and data gathering. Due to the inherent competing objectives of searching for new objects while maintaini
Externí odkaz:
http://arxiv.org/abs/2405.15997
This paper proposes a smooth-trajectory estimator for the labelled multi-Bernoulli (LMB) filter by exploiting the special structure of the generalised labelled multi-Bernoulli (GLMB) filter. We devise a simple and intuitive approach to store the best
Externí odkaz:
http://arxiv.org/abs/2401.00682
Autor:
Chen, Fei, Van Nguyen, Hoa, Leong, Alex S., Panicker, Sabita, Baker, Robin, Ranasinghe, Damith C.
Publikováno v:
Signal Processing (2024)
We consider the problem of tracking multiple, unknown, and time-varying numbers of objects using a distributed network of heterogeneous sensors. In an effort to derive a formulation for practical settings, we consider limited and unknown sensor field
Externí odkaz:
http://arxiv.org/abs/2401.00605
Autor:
Lee, Ji Youn, Shim, Changbeom, Van Nguyen, Hoa, Nguyen, Tran Thien Dat, Choi, Hyunjin, Kim, Youngho
Estimating the trajectories of multi-objects poses a significant challenge due to data association ambiguity, which leads to a substantial increase in computational requirements. To address such problems, a divide-and-conquer manner has been employed
Externí odkaz:
http://arxiv.org/abs/2310.14506
Autor:
Chen, Fei, Van Nguyen, Hoa, Taggart, David A., Falkner, Katrina, Rezatofighi, S. Hamid, Ranasinghe, Damith C.
Today, the most widespread, widely applicable technology for gathering data relies on experienced scientists armed with handheld radio telemetry equipment to locate low-power radio transmitters attached to wildlife from the ground. Although aerial ro
Externí odkaz:
http://arxiv.org/abs/2308.08104
We consider the online planning problem for a team of agents to discover and track an unknown and time-varying number of moving objects from onboard sensor measurements with uncertain measurement-object origins. Since the onboard sensors have limited
Externí odkaz:
http://arxiv.org/abs/2203.04551
The resampling process employed in widely used methods such as Importance Sampling (IS), with its adaptive extension (AIS), are used to solve challenging problems requiring approximate inference; for example, non-linear, non-Gaussian state estimation
Externí odkaz:
http://arxiv.org/abs/2109.13504
This paper proposes an efficient and robust algorithm to estimate target trajectories with unknown target detection profiles and clutter rates using measurements from multiple sensors. In particular, we propose to combine the multi-sensor Generalized
Externí odkaz:
http://arxiv.org/abs/2106.00208
We consider the challenging problem of tracking multiple objects using a distributed network of sensors. In the practical setting of nodes with limited field of views (FoVs), computing power and communication resources, we develop a novel distributed
Externí odkaz:
http://arxiv.org/abs/2012.12990
Tracking and locating radio-tagged wildlife is a labor-intensive and time-consuming task necessary in wildlife conservation. In this article, we focus on the problem of achieving embedded autonomy for a resource-limited aerial robot for the task capa
Externí odkaz:
http://arxiv.org/abs/2007.15860