Chang Liu

Orcid: 0000-0001-7686-2510

Affiliations:
  • University of California at Berkeley, Department of Mechanical Engineering, Vehicle Dynamics and Control Laboratory, CA, USA


According to our database1, Chang Liu authored at least 24 papers between 2015 and 2023.

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Bibliography

2023
Generalized Moving Horizon Estimation for Nonlinear Systems with Robustness to Measurement Outliers.
Proceedings of the American Control Conference, 2023

2022
Primal-dual Estimator Learning: an Offline Constrained Moving Horizon Estimation Method with Feasibility and Near-optimality Guarantees.
CoRR, 2022

Primal-Dual Estimator Learning Method with Feasibility and Near-Optimality Guarantees.
Proceedings of the 61st IEEE Conference on Decision and Control, 2022

2021
Adaptive Online Distributed Optimal Control of Very-Large-Scale Robotic Systems.
IEEE Trans. Control. Netw. Syst., 2021

2020
Mixed Reinforcement Learning with Additive Stochastic Uncertainty.
CoRR, 2020

Rumor-robust Decentralized Gaussian Process Learning, Fusion, and Planning for Modeling Multiple Moving Targets.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019
Scene Understanding in Deep Learning-Based End-to-End Controllers for Autonomous Vehicles.
IEEE Trans. Syst. Man Cybern. Syst., 2019

Learning Recursive Bayesian Nonparametric Modeling of Moving Targets via Mobile Decentralized Sensors.
Proceedings of the International Conference on Robotics and Automation, 2019

2017
How Much Data Are Enough? A Statistical Approach With Case Study on Longitudinal Driving Behavior.
IEEE Trans. Intell. Veh., 2017

Human-Centered Feed-Forward Control of a Vehicle Steering System Based on a Driver's Path-Following Characteristics.
IEEE Trans. Intell. Transp. Syst., 2017

Measurement Dissemination-Based Distributed Bayesian Filter Using the Latest-In-and-Full-Out Exchange Protocol for Networked Unmanned Vehicles.
IEEE Trans. Ind. Electron., 2017

Parallel Interacting Multiple Model-Based Human Motion Prediction for Motion Planning of Companion Robots.
IEEE Trans Autom. Sci. Eng., 2017

Feature Analysis and Selection for Training an End-to-End Autonomous Vehicle Controller Using the Deep Learning Approach.
CoRR, 2017

How Much Data is Enough? A Statistical Approach with Case Study on Longitudinal Driving Behavior.
CoRR, 2017

Feature analysis and selection for training an end-to-end autonomous vehicle controller using deep learning approach.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2017

Pragmatic-Pedagogic Value Alignment.
Proceedings of the Robotics Research, The 18th International Symposium, 2017

Learning a deep neural net policy for end-to-end control of autonomous vehicles.
Proceedings of the 2017 American Control Conference, 2017

Distributed Bayesian filters for multi-vehicle network by using Latest-In-and-Full-Out exchange protocol of measurements.
Proceedings of the 2017 American Control Conference, 2017

Model predictive control-based target search and tracking using autonomous mobile robot with limited sensing domain.
Proceedings of the 2017 American Control Conference, 2017

2016
Generating Plans that Predict Themselves.
Proceedings of the Algorithmic Foundations of Robotics XII, 2016

Dynamical tracking of surrounding objects for road vehicles using linearly-arrayed ultrasonic sensors.
Proceedings of the 2016 IEEE Intelligent Vehicles Symposium, 2016

Goal Inference Improves Objective and Perceived Performance in Human-Robot Collaboration.
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016

Distributed target localization using a group of UGVs under dynamically changing interaction topologies.
Proceedings of the 2016 American Control Conference, 2016

2015
Interacting multiple model-based human motion prediction for motion planning of companion robots.
Proceedings of the 2015 IEEE International Symposium on Safety, 2015


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