1 citations · 2 across the 14 of their papers we have counts for
15 papers
Localization in Spatiotemporal Fields via Environmental PDEs
Jose Fuentes, Abdullah Al Redwan Newaz, Ana Cavalcanti +1
This paper proposes a localization framework that uses spatiotemporal fields governed by partial differential equations (PDEs) as localization signatures. Two PDE classes are consi…
A New Implementation of NeoSLAM and a Comparative Evaluation with RatSLAM
Joao Victor T. Borges, Fabio Coelho, Paulo Padrao +4
This paper presents a new implementation of the NeoSLAM algorithm. The proposed version is a complete rewrite of NeoSLAM into a modular architecture using modern frameworks that, t…
BOWConnect: Parallel Bayesian Optimization over Windows with Learned Local Cost Maps for Sample-Efficient Kinodynamic Motion Planning
Sourav Raxit, Abdullah Al Redwan Newaz, Jose Fuentes +1
This paper presents BOWConnect, a bidirectional parallel kinodynamic motion planner that addresses three fundamental limitations of existing sampling-based methods: sample ineffici…
Muninn: Your Trajectory Diffusion Model But Faster
Gokul Puthumanaillam, Hao Jiang, Ruben Hernandez +4
Diffusion-based trajectory planners can synthesize rich, multimodal robot motions, but their iterative denoising makes online planning and control prohibitively slow. Existing acce…
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).…
Multi-agent Reinforcement Learning for Robotized Coral Reef Sample Collection
Daniel Correa, Tero Kaarlela, Jose Fuentes +3
This paper presents a reinforcement learning (RL) environment for developing an autonomous underwater robotic coral sampling agent, a crucial coral reef conservation and research t…
Enhancing Robot Navigation Policies with Task-Specific Uncertainty Managements
Gokul Puthumanaillam, Paulo Padrao, Jose Fuentes +2
Robots navigating complex environments must manage uncertainty from sensor noise, environmental changes, and incomplete information, with different tasks requiring varying levels o…
TRACE: A Self-Improving Framework for Robot Behavior Forecasting with Vision-Language Models
Gokul Puthumanaillam, Paulo Padrao, Jose Fuentes +6
Predicting the near-term behavior of a reactive agent is crucial in many robotic scenarios, yet remains challenging when observations of that agent are sparse or intermittent. Visi…
GUIDEd Agents: Enhancing Navigation Policies through Task-Specific Uncertainty Abstraction in Localization-Limited Environments
Gokul Puthumanaillam, Paulo Padrao, Jose Fuentes +2
Autonomous vehicles performing navigation tasks in complex environments face significant challenges due to uncertainty in state estimation. In many scenarios, such as stealth opera…
Towards Optimal Human-Robot Interface Design Applied to Underwater Robotics Teleoperation
Paulo Padrao, Jose Fuentes, Tero Kaarlela +2
Efficient and intuitive Human-Robot interfaces are crucial for expanding the user base of operators and enabling new applications in critical areas such as precision agriculture, a…