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pro vyhledávání: '"P. Rathinam"'
Autor:
Rathinam, Arunkumar, Pauly, Leo, Shabayek, Abd El Rahman, Rharbaoui, Wassim, Kacem, Anis, Gaudillière, Vincent, Aouada, Djamila
Multispectral pedestrian detection has gained significant attention in recent years, particularly in autonomous driving applications. To address the challenges posed by adversarial illumination conditions, the combination of thermal and visible image
Externí odkaz:
http://arxiv.org/abs/2411.03576
In this paper, a heuristic for a heterogeneous min-max multi-vehicle multi-depot traveling salesman problem is proposed, wherein heterogeneous vehicles start from given depot locations and need to cover a given set of targets. In the considered probl
Externí odkaz:
http://arxiv.org/abs/2410.23449
Autor:
Bhat, Anoop, Gutow, Geordan, Vundurthy, Bhaskar, Ren, Zhongqiang, Rathinam, Sivakumar, Choset, Howie
The moving target traveling salesman problem with obstacles (MT-TSP-O) is a generalization of the traveling salesman problem (TSP) where, as its name suggests, the targets are moving. A solution to the MT-TSP-O is a trajectory that visits each moving
Externí odkaz:
http://arxiv.org/abs/2409.09852
Autor:
Kumar, Nitesh, Lee, Jaekyung Jackie, Rathinam, Sivakumar, Darbha, Swaroop, Sujit, P. B., Raman, Rajiv
This paper introduces a novel formulation aimed at determining the optimal schedule for recharging a fleet of $n$ heterogeneous robots, with the primary objective of minimizing resource utilization. This study provides a foundational framework applic
Externí odkaz:
http://arxiv.org/abs/2409.00572
Autor:
Sundar, Kaarthik, Rathinam, Sivakumar
We present a novel algorithm that fuses the existing convex-programming based approach with heuristic information to find optimality guarantees and near-optimal paths for the Shortest Path Problem in the Graph of Convex Sets (SPP-GCS). Our method, in
Externí odkaz:
http://arxiv.org/abs/2407.17413
This paper introduces a new formulation that finds the optimum for the Moving-Target Traveling Salesman Problem (MT-TSP), which seeks to find a shortest path for an agent, that starts at a depot, visits a set of moving targets exactly once within the
Externí odkaz:
http://arxiv.org/abs/2403.04917
Autor:
Bhuvaneswari Krishnamoorthy, Shabnam M. Sagar, Aman S. Coonar, Sam Raaj, Akhash V. Rathinam, Rick Air, Sarah Murray, Vanessa Heaslip, Heather Iles-Smith, Narain Moorjani, Sridhar Rathinam
Publikováno v:
Journal of Cardiothoracic Surgery, Vol 19, Iss 1, Pp 1-9 (2024)
Abstract Background The Cardio-Thoracic (CT) professional group experienced a significant increase in stress and workload during and after the COVID-19 pandemic. The Society for Cardiothoracic Surgery (SCTS) in Great Britain and Ireland with the aim
Externí odkaz:
https://doaj.org/article/8def229ffbc94991b50b6f5e8648ff96
In this article, a heuristic is proposed for a min-max heterogeneous multi-vehicle multi-depot traveling salesman problem (TSP), wherein heterogeneous vehicles start from given depot positions and need to cover a given set of targets. The vehicles sh
Externí odkaz:
http://arxiv.org/abs/2312.17403
Autor:
Bhadoriya, Abhay Singh, Rathinam, Sivakumar, Darbha, Swaroop, Casbeer, David W., Manyam, Satyanarayana G.
In this article, we consider a multi-agent path planning problem in a stochastic environment. The environment, which can be an urban road network, is represented by a graph where the travel time for selected road segments (impeded edges) is a random
Externí odkaz:
http://arxiv.org/abs/2312.17340
Multi-Agent Combinatorial Path Finding (MCPF) seeks collision-free paths for multiple agents from their initial to goal locations, while visiting a set of intermediate target locations in the middle of the paths. MCPF is challenging as it involves bo
Externí odkaz:
http://arxiv.org/abs/2312.06314