Trajectory Planning for Soft Robots Using k-NN Graphs and Finite-Element Simulation
DOI:
https://doi.org/10.17979/ja-cea.2026.47.13757Keywords:
Soft robotics, Trajectory and path planning, Modeling and optimization of robotic systems, Numerical methods for optimal controlAbstract
This work presents a methodology to analyze trajectory planning for a soft robot using a workspace generated through SOFA simulation. The set of reachable end-effector positions is represented as a nearest-neighbor graph, where Dijkstra's algorithm is applied with a weighted cost combining geometric distance and actuation cost. By sweeping the weighting parameter α, a family of trajectories between two workspace points is obtained. These trajectories are then evaluated in the path length-actuation cost plane, allowing the identification of non-dominated solutions within the generated set. The results show that the shortest trajectory does not necessarily correspond to the trajectory with the lowest accumulated actuation cost, highlighting the relevance of considering both criteria during planning.
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Copyright (c) 2026 Gerson Lipa, Alberto Rodríguez, Luis Nagua, Cristina García, Sara García, Jorge Muñoz, Concepción A. Monje
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
