Relative Position Estimation for Formation Control with the Fusion of Predicted Future Information and Measurement Data

• Published in: SICE journal of control, measurement, and system integration Online Vol. 13; no. 5; pp. 225 - 232
• Main Authors: Tsuyoshi Ogawa, Kazunori Sakurama, Shintaro Nakatani, Shin-ichiro Nishida
• Format: Journal Article
• Language: English
• Published: Taylor & Francis Group 2020
• Subjects: formation control; multi-robot systems; position estimation
• ISSN: 1884-9970
• DOI: 10.9746/jcmsi.13.225

This paper addresses a relative position estimation problem for formation control of multiple robots. In the authors' previous paper, a relative position estimation method has been proposed, which fuses information from distance sensors and wireless communication. In this method, it is assumed that the robots communicate with others by wireless devices at every control sampling time. Therefore, depending on the performance of the wireless devices, the control sampling time should be set to a large value, which can degrade control performance. In this paper, we propose a new relative position estimation method, which is effective even if the communication sampling time is longer than the control sampling time. The idea in this method is to use predicted information on the time-series of the control input from detected robots. We develop a method to generate the time-series of the predicted control input for successful estimation. Finally, we verify the effectiveness of the proposed method by simulations and an experiment.