MIT ACL - CC-RRT*

Efficient Deep Learning of Robust Policies from MPC via Imitation and Tube-Guided Data Augmentation

Experimental Results for "Efficient Learning of Adaptive Policies via Tube-Guided Data Augmentation"

Tube-NeRF: Efficient Imitation Learning of Vision-based Policies from MPC

EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road Autonomy

[ICRA24] PUMA: Decentr. Uncertainty-aware Multiagent Traj. Planner w/ Image Segmentation Frame Align

[Presentation] Deep-PANTHER: Learning-Based Perception-Aware Traj. Planner in Dynamic Environments

RAMP: A Risk-Aware Mapping and Planning Pipeline for Fast Off-Road Ground Robot Navigation

(TRO 2023) Energy-Aware, Collision-Free Information Gathering for Heterogeneous Robot Teams

Resilient and Distributed Multi-Robot Visual SLAM: Datasets, Experiments, and Lessons Learned

Robust MADER: Decentralized Multiagent Traj Planner Robust to Comm Delay in Dynamic Environments

Probabilistic Traversability Model for Risk-Aware Motion Planning in Off-Road Environments

(ICRA) Robust MADER: Decentralized and Asynchronous Multiagent Traj Planner Robust to Comm Delay

Robust Trajectory Tracking on Insect-Scale Soft-Actuated Aerial Robots with Deep-Learned Tube MPC

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

ICRA 2022 Workshop on Robotic Perception and Mapping: Emerging Techniques

PhD Thesis Defense: Jesus Tordesillas

T-RO/IROS 2021 Presentation: Distributed Certifiably Correct Pose-Graph Optimization

Demonstration-Efficient Guided Policy Search via Imitation of Robust Tube MPC

ICRA 2021: CLIPPER: A Graph-Theoretic Framework for Robust Data Association

ICRA 2021: Efficient Reachability Analysis of Closed-Loop Systems with Neural Network Controllers

L-CSS/ACC 2021: Robustness Analysis of Neural Networks

MINVO Basis: Finding Simplexes with Minimum Volume Enclosing Polynomial Curves

PANTHER: Perception-Aware Trajectory Planner in Dynamic Environments

LION: Lidar-Inertial Observability-Aware Navigator for Vision-Denied Environments