Visual-Aided Obstacle Climbing by Modular Snake Robot

Snake robots, also known as apodal robots, are among the most common and versatile modular robots. Primarily due to their ability to move in different patterns, they can evolve in scenarios with several constraints, some of them hardly accessible to other robot configurations. This paper deals with a specific environment constraint where the robot needs to climb a prismatic obstacle, similar to a step. The objective is to carry out simulations of this function, before implementing it in the physical model. To this end, we propose two different algorithms, parameterized by the obstacle dimensions determined by image processing, and both are evaluated in simulated experiments. The results show that both algorithms are viable for testing in real robots, although more complex scenarios still need to be further studied.