activity
20172022
most citedR-MADDPG for Partially Observable Environments and Limited Communication

64 citations · 101 across the 31 of their papers we have counts for

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5 papers · 1 filter

eess.SY2021

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

Michael Everett, Golnaz Habibi, Jonathan P. How

Neural Networks (NNs) can provide major empirical performance improvements for robotic systems, but they also introduce challenges in formally analyzing those systems' safety prope…

eess.SY2020

Performance Analysis of Adaptive Dynamic Tube MPC

Savva Morozov, Parker C. Lusk, Brett T. Lopez +1

Model predictive control (MPC) is an effective method for control of constrained systems but is susceptible to the external disturbances and modeling error often encountered in rea…

eess.SY2020

Robust Adaptive Control Barrier Functions: An Adaptive & Data-Driven Approach to Safety (Extended Version)

Brett T. Lopez, Jean-Jacques E. Slotine, Jonathan P. How

A new framework is developed for control of constrained nonlinear systems with structured parametric uncertainties. Forward invariance of a safe set is achieved through online para…

eess.SY2019

Dynamic Landing of an Autonomous Quadrotor on a Moving Platform in Turbulent Wind Conditions

Aleix Paris, Brett T. Lopez, Jonathan P. How

Autonomous landing on a moving platform presents unique challenges for multirotor vehicles, including the need to accurately localize the platform, fast trajectory planning, and pr…

eess.SY2019

Dynamic Tube MPC for Nonlinear Systems

Brett T. Lopez, Jean-Jacques E. Slotine, Jonathan P. How

Modeling error or external disturbances can severely degrade the performance of Model Predictive Control (MPC) in real-world scenarios. Robust MPC (RMPC) addresses this limitation…