No More Heavy Lifting: Robotic Solutions to the Container Unloading Problem

This article discusses the scientifically and industrially important problem of automating the process of unloading goods from standard shipping containers. We outline some of the challenges barring further adoption of robotic solutions to this problem, ranging from handling a vast variety of shapes, sizes, weights, appearances, and packing arrangements of the goods, through hard demands on unloading speed and reliability, to ensuring that fragile goods are not damaged. We propose a modular and reconfigurable software framework in an attempt to efficiently address some of these challenges. We also outline the general framework design and the basic functionality of the core modules developed. We present two instantiations of the software system on two different fully integrated demonstrators: (1) coping with an industrial scenario, i.e., the automated unloading of coffee sacks with an already economically interesting performance; and (2) a scenario used to demonstrate the capabilities of our scientific and technological developments in the context of medium- to long-term prospects of automation in logistics. We performed evaluations that allowed us to summarize several important lessons learned and to identify future directions of research on autonomous robots for the handling of goods in logistics applications.

[1]  Morgan Quigley,et al.  ROS: an open-source Robot Operating System , 2009, ICRA 2009.

[2]  Andreas Birk,et al.  Fitting superquadrics in noisy, partial views from a low-cost RGBD sensor for recognition and localization of sacks in autonomous unloading of shipping containers , 2014, 2014 IEEE International Conference on Automation Science and Engineering (CASE).

[3]  Andreas Birk,et al.  The jacobs robotics approach to object recognition and localization in the context of the ICRA'11 Solutions in Perception Challenge , 2012, 2012 IEEE International Conference on Robotics and Automation.

[4]  Erik Schaffernicht,et al.  Support relation analysis and decision making for safe robotic manipulation tasks , 2015, Robotics Auton. Syst..

[5]  Andreas Birk,et al.  Velvet fingers: Grasp planning and execution for an underactuated gripper with active surfaces , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[6]  Achim J. Lilienthal,et al.  Fast and accurate scan registration through minimization of the distance between compact 3D NDT representations , 2012, Int. J. Robotics Res..

[7]  Achim J. Lilienthal,et al.  Comparative evaluation of range sensor accuracy for indoor mobile robotics and automated logistics applications , 2013, Robotics Auton. Syst..

[8]  Andreas Birk,et al.  Robotics and Autonomous Systems , 2022 .

[9]  Vinicio Tincani,et al.  Improving grasp robustness via in-hand manipulation with active surfaces , 2014, ICRA 2014.

[10]  Achim J. Lilienthal,et al.  Automatic relational scene representation for safe robotic manipulation tasks , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[11]  Matei T. Ciocarlie,et al.  Hand Posture Subspaces for Dexterous Robotic Grasping , 2009, Int. J. Robotics Res..

[12]  Christian A. Mueller,et al.  Object shape categorization in RGBD images using hierarchical graph constellation models based on unsupervisedly learned shape parts described by a set of shape specificity levels , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[13]  Vinicio Tincani,et al.  Implementation and control of the Velvet Fingers: A dexterous gripper with active surfaces , 2012, 2013 IEEE International Conference on Robotics and Automation.

[14]  Christian A. Mueller,et al.  Object recognition in RGBD images of cluttered environments using graph-based categorization with unsupervised learning of shape parts , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[15]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Erik Schaffernicht,et al.  Probabilistic relational scene representation and decision making under incomplete information for robotic manipulation tasks , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).