a map. The LiDAR-based SLAM system is always running and
fused with the GNSS localization and odometry.
"The LiDAR is mostly critical in the cabins where the GNSS
availability and reliability is not sufficient," adds Troublé. He
continues, "The full integration with our localization system,
especially the transition from indoor-to-outdoor when the
robot enters a cabin was a challenge. We have tuned and
improved our localization fusion algorithm to get the best out
of each component and deliver a consistent confidence index."
Secure and Safe
As a first step to implementation, the Stanley Robotics team
evaluates the existing car park scope and scale. Historical
parking data is compiled (incoming and outgoing cars) over
the preceding 12 months and run through a simulator to
optimize the number of robots and cabins needed.
Once operational, robot creates its own map in real-time
for every mission by scanning vehicles and adjusting the
dimensions of its ramp accordingly. When ready, Stan clamps
onto the vehicle wheels and with GNSS/LiDAR precision,
navigates from a cabin to a designated parking space for
drop-offs, and vice versa when the customer returns.
Photo Cred.: Stanley Robotics
Photo Cred.: Stanley Robotics
Photo Cred.: Stanley Robotics
