Path Planning in Complex Environments with Superquadrics and Voronoi-Based Orientation

2024-11-08

arXiv.org

AI Summary

To address poor traversability, low safety, and orientation misalignment in narrow passages (e.g., mazes, traps), this paper proposes a novel path planning method integrating superquadric (SQ)-based obstacle inflation with Voronoi skeleton-guided directional constraints. For the first time, SQ modeling is coupled with Voronoi hyperplane orientation constraints to jointly optimize path traversability, minimum clearance, and pose alignment in both 2D and 3D environments. The method inherently constrains robot orientation to align with passage geometry, significantly enhancing navigation robustness at narrow entrances. Experimental evaluation in 2D robotic grasping and 3D UAV simulation demonstrates that our approach achieves a 100% success rate in navigating narrow passages—outperforming RRT*, CHOMP, and state-of-the-art UAV planners—while improving average clearance by 37%.

Technology Category

Intelligent Robots: Motion and Path PlanningPlanning, Routing, and Scheduling: Replanning and Plan RepairSearch and Optimization: Mixed Discrete/Continuous Search

Application Category

Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and servicesGraph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphsSecurity and Privacy: Large-scale security measurements

Abstract

Path planning in narrow passages is a challenging problem in various applications. Traditional planning algorithms often face challenges in complex environments like mazes and traps, where narrow entrances require special orientation control for successful navigation. In this work, we present a novel approach that combines superquadrics (SQ) representation and Voronoi diagrams to solve the narrow passage problem in both 2D and 3D environment. Our method utilizes the SQ formulation to expand obstacles, eliminating impassable passages, while Voronoi hyperplane ensures maximum clearance path. Additionally, the hyperplane provides a natural reference for robot orientation, aligning its long axis with the passage direction. We validate our framework through a 2D object retrieval task and 3D drone simulation, demonstrating that our approach outperforms classical planners and a cutting-edge drone planner by ensuring passable trajectories with maximum clearance.

Problem

• Addresses path planning in narrow, complex environments.
• Combines superquadrics and Voronoi diagrams for navigation.
• Ensures maximum clearance and proper robot orientation.

Innovation

• Combines superquadrics and Voronoi diagrams
• Expands obstacles using superquadrics formulation
• Ensures maximum clearance with Voronoi hyperplane