Modeling Branches for Active Manipulation using Iterative Parameter Estimation

2026-06-17

AI Summary

This study addresses the challenges of modeling and controlling agricultural robots when performing delicate manipulation tasks on plant branches with diverse geometries and material properties within dense foliage. The authors propose an integrated framework that combines physics-based simulation with data-driven iterative parameter estimation. Specifically, tetrahedral mesh models are constructed from point cloud data, and finite element methods are employed to simulate branch deformation. Material parameters are iteratively refined using real-world deformation measurements, enabling a deformation-aware motion planner to generate optimal manipulation trajectories. Evaluated on 30 heterogeneous branches, the approach reduces average deformation energy by 35.69% while increasing path length by only 8.10%, demonstrating significantly enhanced fidelity in physical modeling and active manipulation capability.

Abstract

This study presents a method for modeling diverse plant branches by iteratively estimating material parameters to support delicate branch manipulation. Branch manipulation is necessary in agricultural robotics for plant repositioning, stabilizing, and clearing visual obstructions in dense foliage. The proposed method builds a tetrahedral branch model from point-cloud data and simulates its behavior using the finite element method. Using real observed deformation data, it iteratively estimates branch parameters and then computes an optimal path with a deformation-aware motion planner to move and stabilize branches within another robot's field of view. Across 30 trials on branches with varying geometries and material properties, the proposed method reduced the deformation energy by 35.69% while increasing the path length by 8.10% on average.

Problem

• branch manipulation
• agricultural robotics
• deformation modeling
• material parameter estimation
• visual occlusion

Innovation

• iterative parameter estimation
• branch manipulation
• finite element method
• deformation-aware motion planning
• tetrahedral modeling