Model Predictive Control for Autonomous Navigation Using Embedded Graphics Processing Unit

Abstract The objective of this work is to implement a Model Predictive Control (MPC) algorithm on an embedded Graphics Processing Unit (GPU) card. A MPC model for the autonomous navigation of a ground mobile robot is proposed. GPU CUDA code implementation and CUDA optimization techniques are discussed for this specific problem. The GPU-accelerated application permits extending the prediction horizon and evaluating more future trajectories compared to usual time-constrained CPU implementations. Simulation results and a preliminary experiment are presented to demonstrate the efficiency of the real-time algorithm.

[1]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[2]  Simon See,et al.  Solving Quadratic Programming Problems on Graphics Processing Unit , 2011 .

[3]  Emilio Frazzoli,et al.  Massively parallelizing the RRT and the RRT , 2011, 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  L. Biegler,et al.  Active set vs. interior point strategies for model predictive control , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[5]  Nicolai Fog Gade-Nielsen.  Interior Point Methods on GPU with application to Model Predictive Control , 2014 .

[6]  John Bagterp Jørgensen,et al.  MPC Toolbox with GPU Accelerated Optimization Algorithms , 2012 .

[7]  W. Daniel Hillis,et al.  Data parallel algorithms , 1986, CACM.

[8]  B. Foss,et al.  A new optimization algorithm with application to nonlinear MPC , 2004 .

[9]  Shubhabrata Sengupta,et al.  Efficient Parallel Scan Algorithms for GPUs , 2011 .

[10]  George A. Constantinides,et al.  Tutorial paper: Parallel architectures for model predictive control , 2009, 2009 European Control Conference (ECC).

[11]  Guy Le Besnerais,et al.  Prediction of the scene quality for stereo vision-based autonomous navigation , 2016 .

[12]  Frank Allgöwer,et al.  State and Output Feedback Nonlinear Model Predictive Control: An Overview , 2003, Eur. J. Control.

[13]  Anuradha M. Annaswamy,et al.  Parallelized model predictive control , 2013, 2013 American Control Conference.

[14]  Mark Costello,et al.  Projectile Monte-Carlo Trajectory Analysis Using a Graphics Processing Unit , 2011 .

[15]  Eric W. Frew.  Receding Horizon Control Using Random Search for UAV Navigation with Passive, Non-cooperative Sensing , 2005 .

[16]  Sylvain Bertrand,et al.  MPC Strategies for Cooperative Guidance of Autonomous Vehicles , 2014 .

[17]  Jonathan Rogers.  GPU-enabled projectile guidance for impact area constraints , 2013, Defense, Security, and Sensing.