Abstract
Traversability characteristics of the robot working environment are crucial in planning an efficient path for a robot operating in rough unstructured areas. In the literature, approaches to wheeled or tracked robots can be found, but a relatively little attention is given to walking multi-legged robots. Moreover, the existing approaches for terrain traversability assessment seem to be focused on gathering key features from a terrain model acquired from range data or camera image and only occasionally supplemented with proprioceptive sensing that expresses the interaction of the robot with the terrain. This paper addresses the problem of traversability cost evaluation based on proprioceptive sensing for a hexapod walking robot while optimizing different criteria. We present several methods of evaluating the robot-terrain interaction that can be used as a cost function for an assessment of the robot motion that can be utilized in high-level path-planning algorithms.
Highlights
Exteroceptive sensing is widely analyzed and summarized in the survey [1], where authors conclude that the most favored method is to assess the traversability characteristics before driving the robot into the respective region
According to the survey that provides a study of unmanned ground vehicles (UGV), the generic capability of a robot to negotiate the terrain is the most commonly called as the traversability
If we look at the traversability cost regarding different modality—the energy consumption, we can see that traversing the flat terrain is the least energy consuming
Summary
Exteroceptive sensing is widely analyzed and summarized in the survey [1], where authors conclude that the most favored method is to assess the traversability characteristics before driving the robot into the respective region. Such an assessment is based on a terrain model created from exteroceptive sensors like laser range finder or stereo camera. The difficulties a robot has while traversing rough terrain (e.g., slippages, softness of the ground, energy consumption, etc.) cannot be foreseen in advance. Regarding the mission the robot is requested to accomplish, we need to balance between the time or the distance traveled, the energy consumption, the stability, the danger along the path, etc
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