Global path planner adapts robot movement for different terrains
Global Path Planner with Multi-Model Switching
Robotics
Summary
Robots often need to move across different types of terrain, which can be tricky because their movement depends on the ground. The authors developed a system that helps robots plan and follow paths better by switching between different movement models depending on the terrain and robot state. Their system uses maps that show where the robot can go and plans paths keeping the robot’s direction in mind. They tested their method on robot simulations and showed it works better and uses energy more efficiently.
What this means in practice
- •For robotics engineers: Improve robot navigation by dynamically switching movement models to handle varying terrain and robot conditions.
- •For drone operators: Enhance drone flight path tracking by adapting control models based on terrain features for better efficiency.
Authors
Pietro Gori, Francesco Iotti, Eduard Zelenay, Rastislav Marko, Michele Pierallini, Franco Angelini, Gabriele Pannocchia, Manolo Garabini
Abstract
This work enhances global path planning via a pure-pursuit controller with multi-model kinematic switching that sustains plan fidelity across diverse terrains. The system includes a traversability graph for terrain analysis, a Heading-Aware A* algorithm for generating feasible paths, and a multi-model Pure Pursuit controller for dynamic tracking. A core innovation is adaptive kinematic modeling, enabling real-time switching between kinematic models based on terrain features and robot states. This adaptability optimizes path efficiency and energy use in challenging scenarios. We validate the approach in simulation on different platforms, namely the Artaban quadruped and the X3 quadrotor drone, showcasing improved performance, robustness, and adaptability over standard baselines.