The paper presents an experimental study of resilient path planning for con-tinuum robots taking into account the multi-objective optimisation problem. To do this, we used two well-known algorithms, namely Genetic algorithm and A* algorithm, for path planning and the Analytical Hierarchy Process al-gorithm for paths evaluation. In our experiment Analytical Hierarchy Process algorithm considers four different criteria, i.e. distance, motors damage, me-chanical damage and accuracy each considered to contribute to the resilience of a continuum robot. The use of different criteria is necessary to increasing the time to maintenance operations of the robot. The experiment shows that on the one hand both algorithms can be used in combination with Analytical Hierarchy Process algorithm for multi criteria path-planning, while Genetic algorithm shows superior performance in the comparison of the two algo-rithms.

翻译：本文针对连续型机器人的弹性路径规划问题开展了实验研究，重点考虑了多目标优化场景。研究中采用两种经典算法——遗传算法与A*算法进行路径规划，并引入层次分析法（Analytical Hierarchy Process, AHP）进行路径评估。实验过程中，层次分析法算法考虑了四个不同准则：行驶距离、电机损耗、机械损伤及精度，这些准则均被视为影响连续型机器人弹性的关键因素。采用多准则评估的必要性在于延长机器人的维护保养周期。实验结果表明：一方面，两种算法均可与层次分析法算法相结合实现多准则路径规划；另一方面，在两种算法的对比中，遗传算法展现出更优异的性能表现。