4 accepted papers
This paper extends the family of gap-based local planners to unknown dynamic environments through generating provably collision-free properties for hierarchical navigation systems. Existing perception-informed local planners that operate in dynamic environments rely on emergent or empirical robustne
This study focuses on a layered, experience-based, multi-modal contact planning framework for agile quadrupedal locomotion over a constrained rebar environment. To this end, our hierarchical planner incorporates locomotion-specific modules into the high-level contact sequence planner and performs ki…
Safe quadrupedal navigation through unknown environments is a challenging problem. This paper proposes a hierarchical vision-based planning framework (GPF-BG) integrating our previous Global Path Follower (GPF) navigation system and a gap-based local planner using Bézier curves, so called BBézier Ga…
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…