Guest Editorial: Robotics: Science and Systems 2018 (RSS 2018)
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Guest Editorial: Robotics: Science and Systems 2018 (RSS 2018) Thomas Howard1 · Amanda Prorok2 · Hadas Kress‑Gazit3 Published online: 31 August 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
This special edition of Autonomous Robots (AURO) features papers from the fourteenth Robotics: Science and Systems (RSS) conference. This conference, which brought together researchers for presentation and discussion of cutting-edge research in many areas of robotics, was hosted at Carnegie Music Hall next to Carnegie Mellon University in Pittsburgh, Pennsylvania, USA on June 26–30, 2018. The papers included in this special issue were selected from papers presented at RSS 2018 for their impact and significance to the field of robotics. This issue contains five papers on diverse topics spanning autonomous agricultural robots, human–machine interfaces for human–robot interaction, multi-agent navigation, motion synthesis of robotic manipulators, and route planning under motion constraints. The first paper in this issue is “High Precision Control and Deep Learning-based Corn Stand Counting Algorithms for Agricultural Robot” by Zhongzhong Zhang, Erkan Kayacan, Ben Thompson, and Girish Chowdhary. This paper presents a 3D printed autonomous field robot for agriculture operations that uses a novel deep learning-based approach to automate the measurement of specific plant characteristics. Algorithms for object detection, visual tracking, estimation, navigation, and control are presented along with a detailed description of the TerraSentia robot developed for this purpose. Experimental results show high performance navigation and a vision system capable of performing laborintensive agricultural survey operations without human intervention. The next paper in this issue is “Plug-and-Play Supervisory Control Using Muscle and Brain Signals for Real-Time Gesture and Error Detection” by Joseph DelPreto, Andres F. Salazar-Gomez, Stephanie Gil, Ramin M. Hasani, Frank H. Guenther, and Daniela Rus. This paper introduces a novel * Thomas Howard [email protected] 1
University of Rochester, Rochester, NY, USA
2
University of Cambridge, Cambridge, UK
3
Cornell University, Ithaca, NY, USA
approach to human–robot interaction using electromyography (EMG) and electroencephalography (EEG) biosignals. The technical approach classifies both hand gestures and brain signals to observe and correct robot mistakes when performing specific tasks. Experimental results involving target selection with a Baxter Research Robot with untrained human subjects are presented in this article. The third paper in this special issue is “Planar Max Flow Maps and Determination of Lanes with Clearance” by Renato Farias and Marcelo Kallmann. This paper addresses the problem of route planning via continuous maximum flow in a two-dimensional environment with polygonal obstacles. The proposed approach, which leverages recent advances in GPU programming, optimizes lanes extracted from maximum flow maps to efficiently guide agents between
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