Information-Theoretic Model Predictive Control: Theory and Applications to Autonomous Driving

By Grady Williams, Paul Drews, Brian Goldfain, James M. Rehg, Evangelos A. Theodorou. IEEE Transactions on robotics, 2017

416 citations recorded by the source corpus.

We present an information-theoretic approach to stochastic optimal control problems that can be used to derive general sampling-based optimization schemes. This new mathematical method is used to develop a sampling-based model predictive control algorithm. We apply this information-theoretic model predictive control scheme to the task of aggressive autonomous driving around a dirt test track, and compare its performance with a model predictive control version of the cross-entropy method.

Subfields: Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/287d8bcbeac19e93370200df2620a1ce71a16c81

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In Control and Systems Engineering

Citations in the corpus

Reasoning with Language Model is Planning with World Model (2023, background): “Classical planning methods have been widely adopted in robots and embodied environments [9, 42, 8, 61, 26].”
Safety-Critical Model Predictive Control with Discrete-Time Control Barrier Function (2020, methodology): “her cars in a racing competition, shown in Fig. 1. B. Related Work 1) Model Predictive Control: MPC is widely used for robotic systems, such as autonomous driving, robotic manipulation and locomotion [4]–[6], to achieve optimal performance while satisfying different constraints. One of the most impo”
Reconfigurable Intelligent Surfaces: Principles and Opportunities (2020, background): “V2I networks enable autonomous vehicles (AVs) or connected vehicles (CVs) to receive reliable real-time traffic information from BS, the information is collected by roadside base stations (RBSs) and transmitted from RBSs to BSs, which facilitates the interaction among AVs/CVs and road users, hence e”
Outracing champion Gran Turismo drivers with deep reinforcement learning (2022, neutral): “• Ryota Kokubun: winner 2019 FIA Gran Turismo Nations Cup, Round 5, Tokyo; 3rd place 2020 FIA Gran Turismo Nations Cup.”
An Online Learning Approach to Model Predictive Control (2019, background): “CEM has found applicability in reinforcement learning [19, 21, 26], motion planning [17, 18], and MPC [9, 32].”