Lunar Rover Navigation 1997
Lunar Rover Navigation 1997
The Robotics Institute at Carnegie
Mellon University is developing robotic technologies for planetary
exploration as part of its Lunar Rover
Initiative. Robotic navigational autonomy is a critical capability for
planetary exploration, because the time delay in communication can be many
minutes. Navigational autonomy allows a robot to make progress even in the
absence of communication with Earth.
- See the
Navigation'97 QuickTime video (11 Megabytes)
In 1997, as part of the Atacama Desert Trek field demonstration, the
navigation system onboard the Nomad robot drove autonomously through 21
kilometers of the Atacama Desert in northern Chile. The driest
desert in the world, the Atacama has thousands of square kilometers of
rocky, barren, and varied terrain, which provide the best terrestrial analog
of Moon and Mars-like environments.
Our robot navigation system consisted of three primary components: position
estimation, obstacle detection, and path planning.
- Position Estimation
During the 1997 Atacama Desert Trek, position estimation was provided by
differential GPS, gyrocompass, and inclinometer sensors.
- Obstacle Detection
Obstacle detection was provided by two pairs of rigidly mounted stereo
cameras and the navigation computer. Nomad's stereo vision system had to
have its field of view expanded, because Nomad was almost two and a half
times the width of Ratler, the prototype on which
the stereo vision system was first demonstrated. This was accomplished
using wide angle lenses and a new calibration procedure, for which we
developed a precisely machined, 6 foot tall calibration cube. These tools
resulted in a highly successful deployment. The stereo vision sensors
maintained their calibration, ran successfully for up to nine hours each
day, and were effectively untouched during the 50 days of field
- Path Planning
In the context of the complete navigation system, a pair of images taken by
the stereo cameras is processed into range data in less than one second.
This range data is reprojected into an overhead view, yielding an elevation
map of the area in front of the robot; this is combined with previous
elevation maps using the position estimate. The new elevation map is then
filtered to find all steep slopes, obstacles, dropoffs, and unknown areas.
The planner considers all possible curved paths through the map as far as 10
meters ahead, and marks each one as safe or not-safe.
Armed with the knowledge of path safety, Nomad controlled its direction of
travel in 3 ways. Nomad always chose the safe path and found obstacles on
its own. Unfortunately the software model of the novel steering mechanism
was not complete, so sometimes a human operator had to back Nomad away from
Using Obstacle Avoidance, it drove randomly but safely. At one
point in the desert, Nomad came across an access road and chose it as the
safest route, following the road for nearly 400 meters.
- In Safeguarded Teleoperation, a remote driver provided a preferred
steering direction at each time step; Nomad still chose only safe
directions, but preferred those near the user's direction.
- The final, most-used method was Waypoint Navigation. In this mode the
user specified a point in the world that could be meters or kilometers away.
Nomad drove itself toward the specified point, avoiding obstacles along the
way. During the summer of 1997 this world point was entered by typing
coordinates on a command line, but future versions of the user interface
will allow the user to click on an overhead map view.
The autonomy system was on call throughout the mission, and was typically
run on-demand as circumstances warranted, such as during lunch breaks or
loss of communications). This graph illustrates the daily total distance
traversed in autonomous mode. In summary, Nomad was driven for a total of
21 kilometers of autonomous driving, and 7 kilometers of safeguarded
As NASA plans its future exploration missions, this capability of tens of
kilometers of autonomous traverse will become critical. In the near future,
Carnegie Mellon will enhance the navigation system by adapting sensors to
extremely cold environments, and will send Nomad and future robots to search
for meteorites in Antarctica.