Rong Gu is a Doctoral Student at Mälardalen University since April 2017.
Education Background:
Research:
Since 2017, Rong started his PhD study in MDH. His research is about embedded system design, verification, and validation using formal methods. He is working in the DPAC project group with close cooperation with Volvo Construction Equipment. Currently, his work focuses on applying formal methods to the modelling and verification of autonomous vehicles, which enables finding potential design errors in the early time of development. His research interest is listed but not limited as follows:
Community service as a reviewer: AST(2020), NFM(2020, 2021), FMICS(2019), SERENE(2018, 2019), ISEC(2021), Journal of Robotics
Teaching:
Rong is actively involved in supervising postgraduate students' thesis and teaching the following courses:
He has supervised the following Master thesis:
Research topic:
In an attempt to increase productivity and the workers’ safety, the construction industry is moving towards autonomous construction sites, where various construction equipment operates without human intervention. Such systems are safety-critical and should operate autonomously with very high dependability. On one hand, my research mainly focuses on applying formal verification in the development of autonomous systems, which benefits to find design errors that are difficult to be discovered or reappeared. On the other hand, this research also aims to provide advanced methods and tools to synthesize path and mission plans for multiple autonomous vehicles operating in a closed environment. Those plans can also be simulated and analyzed by using our tools so that the planning conflicts and errors are not delayed to be discovered in practical prototypes or products.
Tool:
The introduction video of our tool called Timed-Automata-based planner for Multiple Autonomous Agents (TAMAA) is on this webpage: click here. TAMAA is connected to a GUI called Mission Management Tool (MMT) designed by Afshin Ameri and Baran Çürüklü.
Recent experience:
Probabilistic Mission Planning and Analysis for Multi-agent Systems (Oct 2020) Rong Gu, Eduard Paul Enoiu, Cristina Seceleanu, Kristina Lundqvist 9th International Symposium On Leveraging Applications of Formal Methods, Verification and Validation (ISoLA 2020)
Verifiable and Scalable Mission-Plan Synthesis for Multiple Autonomous Agents (Sep 2020) Rong Gu, Eduard Paul Enoiu, Cristina Seceleanu, Kristina Lundqvist 25TH INTERNATIONAL CONFERENCE ON FORMAL METHODS FOR INDUSTRIAL CRITICAL SYSTEMS (FMICS)
Automatic Model Generation and Scalable Verification for Autonomous Vehicles (Jun 2020) Rong Gu
Combining Model Checking and Reinforcement Learning for Scalable Mission Planning of Autonomous Agents (May 2020) Rong Gu, Eduard Paul Enoiu, Cristina Seceleanu, Kristina Lundqvist
DPAC Newsletter Spring 2020 (May 2020) Kristina Lundqvist, Mikael Sjödin, Saad Mubeen, Håkan Forsberg, Mikael Ekström, Cristina Seceleanu, Nandinbaatar Tsog, Jakob Danielsson, Mohammad Loni, Baran Çürüklü, LanAnh Trinh, Afshin Ameri E., Luciana Provenzano, Kaj Hänninen, Susanne Fronnå, Marjan Sirjani, Rong Gu, Masoud Daneshtalab, Sima Sinaei, Joakim Lindén
TAMAA: UPPAAL-based Mission Planning for Autonomous Agents (Apr 2020) Rong Gu, Eduard Paul Enoiu, Cristina Seceleanu The 35th ACM/SIGAPP Symposium On Applied Computing (SAC2020)
Project Title | Status |
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DPAC - Dependable Platforms for Autonomous systems and Control | active |