10 papers
Energy-Efficient Multi-Robot Coverage Path Planning of Non-Convex Regions of Interests
Sourav Raxit, Jose Fuentes, Paulo Padrao +4
This letter presents an energy-efficient multi-robot coverage path planning (MRCPP) framework for large, nonconvex Regions of Interest (ROI) containing obstacles and no-fly zones (…
Multi-Robot Trajectory Planning via Constrained Bayesian Optimization and Local Cost Map Learning with STL-Based Conflict Resolution
Sourav Raxit, Abdullah Al Redwan Newaz, Jose Fuentes +3
We address multi-robot motion planning under Signal Temporal Logic (STL) specifications with kinodynamic constraints. Exact approaches face scalability bottlenecks and limited adap…
Bioinspired SLAM Approach for Unmanned Surface Vehicle
Fabio Coelho, Joao Victor T. Borges, Paulo Padrao +4
This paper presents OpenRatSLAM2, a new version of OpenRatSLAM - a bioinspired SLAM framework based on computational models of the rodent hippocampus. OpenRatSLAM2 delivers low-com…
Online Learning of Deceptive Policies under Intermittent Observation
Gokul Puthumanaillam, Ram Padmanabhan, Jose Fuentes +7
In supervisory control settings, autonomous systems are not monitored continuously. Instead, monitoring often occurs at sporadic intervals within known bounds. We study the problem…
Belief-Conditioned One-Step Diffusion: Real-Time Trajectory Planning with Just-Enough Sensing
Gokul Puthumanaillam, Aditya Penumarti, Manav Vora +5
Robots equipped with rich sensor suites can localize reliably in partially-observable environments, but powering every sensor continuously is wasteful and often infeasible. Belief-…
BOW: Bayesian Optimization over Windows for Motion Planning in Complex Environments
Sourav Raxit, Abdullah Al Redwan Newaz, Paulo Padrao +2
This paper introduces the BOW Planner, a scalable motion planning algorithm designed to navigate robots through complex environments using constrained Bayesian optimization (CBO).…