General Object Tip Detection and Pose Estimation for Robot Manipulation

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Shukla D., ERKENT Ö., Piater J.

10th International Conference on Computer Vision Systems (ICVS), Copenhagen, Denmark, 6 - 09 July 2015, vol.9163, pp.364-374 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 9163
  • Doi Number: 10.1007/978-3-319-20904-3_33
  • City: Copenhagen
  • Country: Denmark
  • Page Numbers: pp.364-374
  • Keywords: Pose estimation, Tool tip detection, Peg-in-hole insertion, IMAGE MOMENTS
  • Hacettepe University Affiliated: No


Robot manipulation tasks like inserting screws and pegs into a hole or automatic screwing require precise tip pose estimation. We propose a novel method to detect and estimate the tip of elongated objects. We demonstrate that our method can estimate tip pose to millimeter-level accuracy. We adopt a probabilistic, appearance-based object detection framework to detect pegs and bits for electric screw drivers. Screws are difficult to detect with feature-or appearance-based methods due to their reflective characteristics. To overcome this we propose a novel adaptation of RANSAC with a parallel-line model. Subsequently, we employ image moments to detect the tip and its pose. We show that the proposed method allows a robot to perform object insertion with only two pairs of orthogonal views, without visual servoing.