Grid-Based Motion Planning Using Advanced Motions for Hexapod Robots

This paper presents the motion planning framework for a hexapod, based on advanced motions, for accessing challenging spaces, namely narrow pathways and large holes, both of which are surrounded by walls. The advanced motions, wall and chimney walking, utilise environment surfaces that are perpendicular to the ground plane to support the robot motion. Such techniques have not yet been studied in the literature. The hierarchical planning framework proposed here is an extension to existing approaches which have only considered ground walking where foothold contacts are confined to the ground plane. During the pre-processing phase of the 2.5D grid map, the motion primitives employed are assessed for each cell and stacked to the graph if valid. The A* algorithm is then used to find a path to the goal position. Following that, the path is post-processed to smoothen the motions and generate a continuous path. Footholds are then selected along the path. The framework has been evaluated in simulation on the custom-designed Corin hexapod. The resulting path enables access to areas that are previously thought to be inaccessible and reduces the travelling distance compared to previous studies.

I. Introduction

The exploration and mapping of unknown extreme environments is considered as a typical and an important example of the many uses of legged robots. This may find its application in search and rescue, nuclear decommissioning, and demining missions [1]. Although far superior to wheeled vehicles, the locomotion of legged robots in extreme environments is a complex and challenging endeavour. For example, in a disaster-response situation, the robot may have to traverse over rough and uneven terrain, climb over obstacles, and walk in narrow passageways [2]. This specifies high requirements for the robot in terms of manoeuvrability.