• Ocean and Polar Research
• /
• v.36 no.4
• /
• pp.465-473
• /
• 2014

This paper proposes a formation control method by which multi-mining robots maintain a specified formation and follow a path. To secure the path tracking performance, a pure-pursuit algorithm is considered for each individual robot, and to minimize the deviation from the reference path, speed reduction in the steering motion is added. For the formation, in which two robots are parallel in a lateral direction, the robots track the specified path at a constant distance. In this way, the Leader-Follower method is adopted and the following robot knows the position and heading angle of the leader robot. Through the experimental test using two ground vehicle models, the performance is verified.

• Asian Journal of Innovation and Policy
• /
• v.8 no.1
• /
• pp.73-96
• /
• 2019

This study suggests a new approach for identifying core robot tech-nologies based on technological cross-impact. Specifically, the approach applies data mining techniques and multi-criteria decision-making methods to the co-classification information of registered patents on the robots. First, a cross-impact matrix is constructed with the confidence values by applying association rule mining (ARM) to the co-classification information of patents. Analytic network process (ANP) is applied to the co-classification frequency matrix for deriving weights of each robot technology. Then, a technique for order performance by similarity to ideal solution (TOPSIS) is employed to the derived cross-impact matrix and weights for identifying core robot technologies from the overall cross-impact perspective. It is expected that the proposed approach could help robot technology managers to formulate strategy and policy for technology planning of robot area.