  Industrial robots are increasingly used in various applications where the
robot accuracy becomes very important, hence calibrations of the robot's
kinematic parameters and the measurement system's extrinsic parameters are
required. However, the existing calibration approaches are either too
cumbersome or require another expensive external measurement system such as
laser tracker or measurement spinarm. In this paper, we propose SCALAR, a
calibration method to simultaneously improve the kinematic parameters of a
6-DoF robot and the extrinsic parameters of a 2D Laser Range Finder (LRF) which
is attached to the robot. Three flat planes are placed around the robot, and
for each plane the robot moves to several poses such that the LRF's ray
intersect the respective plane. Geometric planar constraints are then used to
optimize the calibration parameters using Levenberg- Marquardt nonlinear
optimization algorithm. We demonstrate through simulations that SCALAR can
reduce the average position and orientation errors of the robot system from
14.6mm and 4.05 degrees to 0.09mm and 0.02 degrees.
