4 accepted papers
Humanoid robots possess the ability to perform complex tasks in challenging environments. However, they require a model of the surroundings in a representation that is sufficient enough for downstream tasks such as footstep planning. The maps generated by existing mapping algorithms are either spars…
For achieving significant levels of autonomy, legged robot behaviors require perceptual awareness of both the terrain for traversal, as well as structures and objects in their surroundings for planning, obstacle avoidance, and high-level decision making. In this work, we present a perception engine…
Legged robots require fast and accurate representation of their surrounding terrain to achieve behaviors such as running, push recovery, continuous walking, backflips, while also utilizing on-board computational resources efficiently. The desired tasks can be achieved efficiently by representing the…
Awareness of the environment is essential for mobile robots. Perception for legged robots requires high levels of reliability and accuracy in order to walk stably in the types of complex, cluttered environments we are interested in. In this paper, we present a usable environmental perception algorit…