RGB–D terrain perception and dense mapping for legged robots

Visual Terrain Classification For Legged Robots

Visual Terrain Classification For Legged Robots Paul Filitchkin Recent work in terrain classification has relied largely on 3D sensing methods and color based classification. We present an approach that works with a single, compact camera and maintains high classification rates that are robust to changes in illumination. Terrain is classified using a bag of visual words (BOVW) created from spee...

Motion Planning for Legged Robots on Varied Terrain

This paper studies the quasi-static motion of large legged robots that have many degrees of freedom. While gaited walking may suffice on easy ground, rough and steep terrain requires unique sequences of footsteps and postural adjustments specifically adapted to the terrain’s local geometric and physical properties. This paper presents a planner that computes these motions by combining graph sea...

Legged robots on rough terrain: experiments in adjusting step length

To travel on rough terrain, a legged system must use the available footholds, even when they are isolated or hidden by obstacles. This thesis addresses the task of adjusting the length of each step to place the feet on available footholds, in the context of a dynamic biped robot that actively balances itself as it runs. In order for the biped to use specific footholds, the control system must s...

Accurate tracking of legged robots on natural terrain

Statically stable walking locomotion research has focused mainly on robot design and gait generation. However, there is a need to expand robots’ capabilities so that walking machines can accomplish the kinds of real tasks for which they are eminently suited. Many such tasks demand trajectory tracking, but researchers have traditionally ignored this subject. This article focuses on the tracking ...

Terrain Mapping for Outdoor Robots: Robust Perception for Walking in the Grass