A Hybrid Primitive-Based Planner for Autonomous Navigation with CENTAURO Robot

EasyChair Preprint 9352

Abstract

Wheeled-legged robots have the ability to navigate in cluttered and irregular environments adapting the locomotion mode to the terrain perceived. To achieve this functionality, a locomotion planner is needed. In this work we present a hybrid search-based planner, which considers a set of modifiable motion primitives and a 2.5D traversability map acquired from the environment to generate navigation plans for the hybrid mobility robot CENTAURO. Our approach was validated in simulation and on the real wheeled-legged robot CENTAURO, demonstrating traversing capabilities in cluttered environments with various obstacles.

Keyphrases: Legged robots, Motion and Path Planning, Sensor-based Control

@booklet{EasyChair:9352,
  author    = {Alessio De Luca and Luca Muratore and Nikos Tsagarakis},
  title     = {A Hybrid Primitive-Based Planner for Autonomous Navigation with CENTAURO Robot},
  howpublished = {EasyChair Preprint 9352},
  year      = {EasyChair, 2022}}