Jonathan How

Massachusetts Institute of Technology

United States

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Articles (20)

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2022

Collaborators (9)

George Pappas

Professor

University of Pennsylvania

UNITED STATES

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Mykel Kochenderfer

Associate Professor

Stanford University

UNITED STATES

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Jiuguang Wang

UNITED STATES

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Sildomar Monteiro

Massachusetts Institute of Technology

UNITED STATES

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Bernadette Bucher

Assistant Professor

University of Michigan

UNITED STATES

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Nikolay Atanasov

Assistant Professor

University of California, San Diego

UNITED STATES

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David Matthew Rosen

Assistant Professor

Northeastern University

UNITED STATES

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Michael Everett

Northeastern University

UNITED STATES

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Yun Chang

Massachusetts Institute of Technology

UNITED STATES

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Jonathan How

Research Interests

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Articles (20)

SDP Synthesis of Distributionally Robust Backward Reachable Trees for Probabilistic Planning

Safe Autonomy for Uncrewed Surface Vehicles Using Adaptive Control and Reachability Analysis

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

MURP: Multi-Agent Ultra-Wideband Relative Pose Estimation With Constrained Communications in 3D Environments

Tube-NeRF: Efficient Imitation Learning of Visuomotor Policies From MPC via Tube-Guided Data Augmentation and NeRFs

Finding the optimal exploration-exploitation trade-off online through Bayesian risk estimation and minimization

CLIPPER: Robust Data Association Without an Initial Guess

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

Certifiably Correct Range-Aided SLAM

Constraint-Aware Refinement for Safety Verification of Neural Feedback Loops

Incremental Non-Gaussian Inference for SLAM Using Normalizing Flows

Backward Reachability Analysis of Neural Feedback Loops: Techniques for Linear and Nonlinear Systems

Energy-Aware, Collision-Free Information Gathering for Heterogeneous Robot Teams

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

GraffMatch: Global Matching of 3D Lines and Planes for Wide Baseline LiDAR Registration

MIXER: Multiattribute, Multiway Fusion of Uncertain Pairwise Affinities

MINVO Basis: Finding Simplexes with Minimum Volume Enclosing Polynomial Curves

Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning

Kimera-Multi: Robust, Distributed, Dense Metric-Semantic SLAM for Multi-Robot Systems

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

Collaborators (9)

George Pappas

Mykel Kochenderfer

Jiuguang Wang

Sildomar Monteiro

Bernadette Bucher

Nikolay Atanasov

David Matthew Rosen

Michael Everett

Yun Chang

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