Image-Based Method for Determining Better Walking Strategies for Hexapods

Abstract

An intelligent walking strategy is vital for multi-legged robots possessing no a priori information of an environment when traversing across discontinuous terrain. Six-legged robots outperform other multi-legged robots in static and dynamic stability. However, hexapods require careful planning to traverse across discontinuous terrain. A hexapod walking strategy can be accomplished using a vision-based navigation system to identify the surrounding environment. This paper presents an image-based technique to achieve better walking strategies for a hexapod walking on a special terrain containing irregular, restricted regions. The properties of the restricted regions were acquired beforehand by using reliable surveillance means. Moreover, simplified forward gaits, better rotational gaits, and adaptive gait selection strategies for walking on discontinuous terrain were proposed. The hexapod can effectively switch the gait sequences and types according to the environment involved. The boundary of standing zones can be successfully labelled by applying the greyscale erosion comprising a structuring element similar in shape and size to the foot tip of the hexapod. The experimental results demonstrated that the proposed image-based technique significantly improved the walking strategies of hexapods traversing on discontinuous terrain.