Imagenet large scale visual recognition challenge (ILSVRC) has increased the image recognition ability based on machine learning including Deep Neural Network, whereas Amazon Picking or Robotics Challenge has demonstrated that the image recognition methods are useful for robots to pick and place many types of objects. Pick and place does not require accurate motion control, and the next challenge thus should involve the requirements for high motion accuracy. In this context, World Robot Summit industry category (WRS) was held to pursue the robot ability for completing a complex assembly task. However, even top teams did complete only several parts of the assembly tasks. It indicates a large gap between robots and human at assembling ability. It also indicates the current limitations and potentials of robotic assembly technologies, namely the technologies that requires to be advanced as a next step. To build up the next technologies, the reviewing of current state-of-the-art technologies are necessary. Based on this, this workshop aims at clarifying the current limits and potentials at robotic assembly by investigating the state-of-art technologies for robotic assembly as well as the assembly challenge program results, to accelerate the generation of new methodologies, strategies, and techniques for automatizing robotic assembly.