MASTER´S THESIS: Robot and Human Pose Estimation with Deep Learning

Sista ansökan


Finding the pose of a human within an image has a multitude of applications, such as human-machine interaction (gesture recognition, gaming), action recognition, positioning. An important application field for SICK is collaborative robotics where humans and robots can work next to each other. From a safety perspective it is of interest to map the human and robot positions in order to avoid collisions and injuries.

The task in this Master’s Thesis is to investigate a Deep Learning-based system that jointly finds the pose of a human and a robot arm in an image for this purpose.

 Problems to address include:

  • Automatic collection of ground truth data for the robot arm pose detection
  • Evaluation of Deep Learning architectures
  • Evaluation of system performance


For more information, contact R&D manager Ola Friman ( and apply below at "ANSÖKAN"  before  the 19th of October. Please notice: Application must include CV, Cover letter and LADOK (study results including courses)

Ansvarig rekryterare

Mikael Sundh


Annonsen är avslutad och det går inte längre att ansöka.

Följ oss via våra sociala kanaler!