A multirange architecture for collision-free off-road robot navigation

Pierre Sermanet, Raia Hadsell, Marco Scoffier, Matt Grimes, Jan Ben, Ayse Erkan, Chris Crudele, Urs Miller, Yann LeCun

Research output: Contribution to journalArticlepeer-review


We present a multilayered mapping, planning, and command execution system developed and tested on the LAGR mobile robot. Key to robust performance under uncertainty is the combination of a short-range perception system operating at high frame rate and low resolution and a long-range, adaptive vision system operating at lower frame rate and higher resolution. The short-range module performs local planning and obstacle avoidance with fast reaction times, whereas the long-range module performs strategic visual planning. Probabilistic traversability labels provided by the perception modules are combined and accumulated into a robot-centered hyperbolic-polarmap with a 200-m effective range. Instead of using a dynamical model of the robot for short-range planning, the system uses a large lookup table of physically possible trajectory segments recorded on the robot in a wide variety of driving conditions. Localization is performed using a combination of global positioning system, wheel odometry, inertial measurement unit, and a high-speed, low-complexity rotational visual odometry module. The end-to-end system was developed and tested on the LAGR mobile robot and was verified in independent government tests.

Original languageEnglish (US)
Pages (from-to)52-87
Number of pages36
JournalJournal of Field Robotics
Issue number1
StatePublished - Jan 2009

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications


Dive into the research topics of 'A multirange architecture for collision-free off-road robot navigation'. Together they form a unique fingerprint.

Cite this