Traversability illustrates the difficulty of driving through a specific region and encompasses
the suitability of the terrain for traverse based on its physical properties, such as slope and …

In this work, we show how to learn a visual walking policy that only uses a monocular RGB
camera and proprioception. Since simulating RGB is hard, we necessarily have to learn …

We present a self-supervised approach for learning to predict traversable paths for wheeled
mobile robots that require good traction to navigate. Our algorithm, termed WayFAST …

Understanding the terrain in the upcoming path of a ground robot is one of the most
challenging problems in field robotics. Terrain and traversability analysis is a …

This work reports ondeveloping a deep inverse reinforcement learning method for legged
robots terrain traversability modeling that incorporates both exteroceptive and proprioceptive …

Estimating the traversability of terrain should be reliable and accurate in diverse conditions
for autonomous driving in off-road environments. However, learning-based approaches …

Navigation planning for legged robots has distinct challenges compared to wheeled and
tracked systems due to the ability to lift legs off the ground and step over obstacles. While …

To achieve successful field autonomy, mobile robots need to freely adapt to changes in their
environment. Visual navigation systems such as Visual Teach and Repeat (VT&R) often …

The work presents a review on ongoing researches in terrain-related challenges influencing
the navigation of Autonomous Robots, specifically Unmanned Ground ones. The paper aims …

This letter presents a prediction algorithm of driving energy for future Mars rover missions.
The majority of future Mars rovers would be solar-powered, which would require energy …