MPPI-IPDDP: Hybrid Method of Collision-Free Smooth Trajectory Generation for Autonomous Robots

Authors: Min-Gyeom Kim, Minchan Jung, JunGee Hong, Kwang-Ki K. Kim

Published: 2022 (Journal Paper)

Source: Transactions on Industrial Informatics

Algorithm: MPPI-IPDDP

arXiv: 2208.02439

DOI: 10.1109/TII.2024.3507940

Summary

Hybrid method combining MPPI for global, collision-free trajectory generation with Interior Point DDP (IPDDP) for smooth, dynamically optimal local refinement, leveraging the complementary strengths of sampling and gradient-based trajectory optimization.

Abstract

This paper presents a hybrid trajectory optimization method designed to generate collision-free, smooth trajectories for autonomous mobile robots. By combining sampling-based Model Predictive Path Integral (MPPI) control with gradient-based Interior-Point Differential Dynamic Programming (IPDDP), we leverage their respective strengths in exploration and smoothing. The proposed method, MPPI-IPDDP, involves three steps: First, MPPI control is used to generate a coarse trajectory. Second, a collision-free convex corridor is constructed. Third, IPDDP is applied to smooth the coarse trajectory, utilizing the collision-free corridor from the second step. To demonstrate the effectiveness of our approach, we apply the proposed algorithm to trajectory optimization for differential-drive wheeled mobile robots and point-mass quadrotors. In comparisons with other MPPI variants and continuous optimization-based solvers, our method shows superior performance in terms of computational robustness and trajectory smoothness.

Links

Primary

Paper arxiv.org

Standard

arXiv Abstract 2208.02439 arXiv PDF 2208.02439 arXiv HTML 2208.02439 DOI 10.1109/TII.2024.3507940

Alternate

ieeexplore.ieee.org ieeexplore.ieee.org GitHub: i-ASL/mppi-ipddp github.com youtube.com youtube.com

Tags

• Trajectory optimization

• MPPI

• Differential dynamic programming

• Interior point

• Collision avoidance

• Hybrid trajectory optimization