| Original language | English |
|---|---|
| Article number | 9444594 |
| Pages (from-to) | 5613-5617 |
| Number of pages | 5 |
| Journal | IEEE Robotics and Automation Letters |
| Volume | 6 |
| Issue number | 3 |
| DOIs | |
| State | Published - Jul 2021 |
| Externally published | Yes |
Keywords
- Human motion prediction
- motion planning
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In: IEEE Robotics and Automation Letters, Vol. 6, No. 3, 9444594, 07.2021, p. 5613-5617.
Research output: Contribution to journal › Editorial
TY - JOUR
T1 - Guest Editorial
T2 - Introduction to the Special Issue on Long-Term Human Motion Prediction
AU - Palmieri, Luigi
AU - Andrey, Rudenko
AU - Mainprice, Jim
AU - Hanheide, Marc
AU - Alahi, Alexandre
AU - Lilienthal, Achim
AU - Arras, Kai O.
N1 - Funding Information: Marc Hanheide is a Professor of Intelligent Robotics and Interactive Systems in the School of Computer Science at the University of Lincoln, U.K.. He received the Diploma and Ph.D. degrees (Dr.-Ing.) in computer science from Bielefeld University, Germany, in 2001 and 2006, respectively. From 2006 to 2009 he held a position as a Senior Researcher in the Applied Computer Science Group. From 2009 until 2011, he was a Research Fellow at the School of Computer Science at the University of Birmingham, U.K.. Marc Hanheide is a Principle Investigator in many national and international research projects, funded by H2020, EPSRC, InnovateUK, DFG, industry partners, and others. The STRANDS, ILIAD, RASberry, and NCNR projects are among the bigger projects he is involved with. In all his work, he researches on autonomous robots, human-robot interaction, interaction-enabling technologies, and system architectures. Marc Hanheide specifically focuses on aspects of long-term robotic behaviour and human-robot interaction and adaptation. Funding Information: Alexandre Alahi is currently an Assistant Professor at EPFL. He spent five years at Stanford University as a Post-doc and Research Scientist after obtaining his Ph.D. from EPFL. His research enables machines to perceive the world and make decisions in the context of transportation problems and Smart Environments. He has worked on the theoretical challenges and practical applications of socially-aware Artificial intelligence, i.e., systems equipped with perception and social intelligence. He was awarded the Swiss NSF (Swiss National Science Foundation) early and advanced Researcher grants for his work on predicting human social behavior. He won the CVPR Open Source Award (2012) for his work on Retina-inspired image descriptors, and the ICDSC Challenge Prize (2009) for his sparsity-driven Algorithm that has tracked more than 100 million pedestrians to date. Funding Information: This work has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant agreement No. 732737 (ILIAD).
PY - 2021/7
Y1 - 2021/7
KW - Human motion prediction
KW - motion planning
UR - http://www.scopus.com/inward/record.url?scp=85107593843&partnerID=8YFLogxK
U2 - 10.1109/LRA.2021.3077964
DO - 10.1109/LRA.2021.3077964
M3 - Editorial
AN - SCOPUS:85107593843
SN - 2377-3766
VL - 6
SP - 5613
EP - 5617
JO - IEEE Robotics and Automation Letters
JF - IEEE Robotics and Automation Letters
IS - 3
M1 - 9444594
ER -