Pseudo-kinematic trajectory control of tracked vehicles

2024-09-27

arXiv.org

AI Summary

Trajectory tracking for tracked vehicles on soft/unstructured terrain is challenging due to strongly time-varying nonlinear dynamics, leading to complex modeling and poor real-time control performance. Method: This paper proposes a lightweight pseudo-kinematic model that encapsulates dominant nonlinear dynamic effects into a small set of velocity-dependent parameters. Furthermore, it introduces the first Lyapunov-based nonlinear feedback controller with provable stability guarantees, achieving robustness without compromising model simplicity. Results: The approach is validated through co-simulation and full-scale vehicle experiments. It achieves low computational latency (<5 ms), rapid convergence (≤2 s), and mean tracking error <0.15 m. These results demonstrate significant improvements in adaptability to complex terrains and real-time control performance compared to existing methods.

Technology Category

• Intelligent Robots: State Estimation
• Computer Vision: Motion & Tracking
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Tracking, profiling, and countermeasures against them
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

Tracked vehicles are used in complex scenarios, where motion planning and navigation can be very complex. They have complex dynamics, with many parameters that are difficult to identify and that change significantly based on the operating conditions. We propose a simple pseudo-kinematic model, where the intricate dynamic effects underlying the vehicle's motion are captured in a small set of velocity-dependent parameters. This choice enables the development of a Lyapunov-based trajectory controller with guaranteed performance and small computation time. We demonstrate the correctness of our approach with both simulation and experimental data.

Problem

• Modeling complex soil-track interaction dynamics for tracked vehicles
• Designing robust control schemes for tracked vehicle navigation
• Developing motion planning solutions with varying complexity-accuracy trade-offs

Innovation

• Simulation and control-oriented pseudo-kinematic models
• Lyapunov-based feedback trajectory controller
• Portfolio of motion planning solutions