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Jesus Tordesillas

7 accepted papers

2025

FOCI: Trajectory Optimization on Gaussian Splats

IROS 2025

3D Gaussian Splatting (3DGS) has recently gained popularity as a faster alternative to Neural Radiance Fields (NeRFs) in 3D reconstruction and view synthesis methods. Leveraging the spatial information encoded in 3DGS, this work proposes FOCI (Field Overlap Collision Integral), an algorithm that is

Cited by 2SourceScholar
2025

PRIMER: Perception-Aware Robust Learning-Based Multiagent Trajectory Planner

ICRA 2025

In decentralized multiagent trajectory planners, agents need to communicate and exchange their positions to generate collision-free trajectories. However, due to localization errors/uncertainties, trajectory deconfliction can fail even if trajectories are perfectly shared between agents. To address

Cited by 1SourceScholar
2024

Robust MADER: Decentralized Multiagent Trajectory Planner Robust to Communication Delay in Dynamic Environments

RA-L 2024

Communication delays can be catastrophic for multiagent systems. However, most existing state-of-the-art multiagent trajectory planners assume perfect communication and therefore lack a strategy to rectify this issue in real-world environments. To address this challenge, we propose Robust MADER (RMA

Cited by 20SourcecodeScholar
2023

Deep-PANTHER: Learning-Based Perception-Aware Trajectory Planner in Dynamic Environments

RA-L 2023

This letter presents Deep-PANTHER, a learning-based perception-aware trajectory planner for unmanned aerial vehicles (UAVs) in dynamic environments. Given the current state of the UAV, and the predicted trajectory and size of the obstacle, Deep-PANTHER generates multiple trajectories to avoid a dyna

Cited by 46SourcecodeScholar
2023

Robust MADER: Decentralized and Asynchronous Multiagent Trajectory Planner Robust to Communication Delay

ICRA 2023poster

Although communication delays can disrupt multiagent systems, most of the existing multiagent trajectory planners lack a strategy to address this issue. State-of-the-art approaches typically assume perfect communication environments, which is hardly realistic in real-world experiments. This paper pr…

Cited by 18SourceScholar
2019

FASTER: Fast and Safe Trajectory Planner for Flights in Unknown Environments

IROS 2019poster

High-speed trajectory planning through unknown environments requires algorithmic techniques that enable fast reaction times while maintaining safety as new information about the operating environment is obtained. The requirement of computational tractability typically leads to optimization problems…

Cited by 221SourceScholar
2019

Real-Time Planning with Multi-Fidelity Models for Agile Flights in Unknown Environments

ICRA 2019poster

Autonomous navigation through unknown environments is a challenging task that entails real-time localization, perception, planning, and control. UAVs with this capability have begun to emerge in the literature with advances in lightweight sensing and computing. Although the planning methodologies va…

Cited by 50SourceScholar