Ramanarayan Vasudevan

Associate Professor

University of Michigan

United States

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Ramanarayan Vasudevan is an Associate Professor at the University of Michigan, United States. His research areas include trajectory optimization, autonomous vehicle perception, and safe motion planning for manipulators under uncertainty. Recently, he has published articles on topics such as risk-aware trajectory design and reachability in dynamical systems.

Articles (19)

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2021

Assistant Professor

University of North Carolina at Chapel Hill

UNITED STATES

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Katherine A. Skinner

University of Michigan

UNITED STATES

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Ramanarayan Vasudevan

Research Interests

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Articles (19)

Let us Make a Splan: Risk-Aware Trajectory Optimization in a Normalized Gaussian Splat

Bring the Heat: Rapid Trajectory Optimization With Pseudospectral Techniques and the Affine Geometric Heat Flow Equation

Can Not Touch This: Real-Time, Safe Motion Planning and Control for Manipulators Under Uncertainty

Dataset and Benchmark: Novel Sensors for Autonomous Vehicle Perception

Reachable Sets of Homogeneous Polynomial Dynamical Systems Using Exact Solutions

A Regret-Informed Evolutionary Approach for Generating Adversarial Scenarios for Black-Box Off-Road Autonomy Systems

Controllability and Observability of Temporal Hypergraphs

REFINE: Reachability-Based Trajectory Design Using Robust Feedback Linearization and Zonotopes

Serving Time: Real-Time, Safe Motion Planning and Control for Manipulation of Unsecured Objects

CLONeR: Camera-Lidar Fusion for Occupancy Grid-Aided Neural Representations

Predicting Sagittal-Plane Swing Hip Kinematics in Response to Trips

These Maps are Made for Walking: Real-Time Terrain Property Estimation for Mobile Robots

A Kinematic Model for Trajectory Prediction in General Highway Scenarios

Koopman-Based Control of a Soft Continuum Manipulator Under Variable Loading Conditions

Sensor Switching Control Under Attacks Detectable by Finite Sample Dynamic Watermarking Tests

Detecting Generalized Replay Attacks via Time-Varying Dynamic Watermarking

Advantages of Bilinear Koopman Realizations for the Modeling and Control of Systems With Unknown Dynamics

Data-Driven Control of Soft Robots Using Koopman Operator Theory

Safe, Optimal, Real-Time Trajectory Planning With a Parallel Constrained Bernstein Algorithm

Collaborators (9)

Daniel Bruder

C David Remy

Manikandasriram Srinivasan Ramanagopal

Matthew Johnson-Roberson

Anil Aswani

Anqi Dong

Brent Gillespie

Can Chen

Katherine A. Skinner

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