Sharan Nayak — accepted AI-conference papers

2023

A Heuristic-Guided Dynamical Multi-Rover Motion Planning Framework for Planetary Surface Missions

Sharan Nayak, Michael Paton, Michael W. Otte

RA-L 2023

We present a heuristic-guided multi-robot motion planning framework that solves the problem of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> dynamical agents visiting <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://

Cited by 12 Source ↗Scholar ↗

2020

Experimental Comparison of Decentralized Task Allocation Algorithms Under Imperfect Communication

Sharan Nayak, Michael W. Otte, Suyash Yeotikar, Estefany Carrillo, Eliot Rudnick-Cohen, Mohamed Khalid M. Jaffar +4

RA-L 2020

We compare the performance of five state of the art decentralized task allocation algorithms under imperfect communication conditions. The decentralized algorithms we consider are CBAA, ACBBA, DHBA, HIPC and PI. All algorithms are evaluated using three different models of communication, including th

Cited by 47 Source ↗Scholar ↗