Resilient Movement Planning for Continuum Robots

Abstract

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 algorithm for paths evaluation. In our experiment Analytical Hierarchy Process algorithm considers four different criteria, i.e. distance, motors damage, mechanical 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 algorithms.

Figures (8)

• Figure 1: Self-built tendon-driven continuum robot prototype.
• Figure 2: Robot’s environment for one section.
• Figure 3: Alternative goal points.
• Figure 4: Criteria analysis results. Each line shows the generated path for a particular criteria combination group (Group index). Different paths are highlighted with different colors. Column “GA path” shows final results of the GA. Column “A* path” shows final results of the A* algorithm. Comparing both columns clearly shows that GA provides a higher variety of paths.
• Figure 5: “Single goal point” Experiment: a) Processing Time b) Relation of solutions with better fitness: A* better than GA (blue), both yielding the same results (black).