Abstract—This paper introduces a new method to determine
a person’s pose based on laser range measurements. Such
estimates are typically a prerequisite for any human-aware
robot navigation, which is the basis for effective and timeextended
interaction between a mobile robot and a human.
The robot uses observed information from a laser range finder
to detect persons and their position relative to the robot. This
information together with the motion of the robot itself is fed
through a Kalman filter, which utilizes a model of the human
kinematic movement to produce an estimate of the person’s
pose. The resulting pose estimates are used to identify humans
who wish to be approached and interacted with. The interaction
motion of the robot is based on adaptive potential functions
centered around the person that respect the persons social
spaces. The method is tested in experiments that demonstrate
the potential of the combined pose estimation and adaptive
potential function approach.