Lorenzo Nardi

PhD Student
Contact:
Email: lorenzo.nardi@nulluni-bonn.de
Tel: +49 - 228 - 73 - 27 11
Fax: +49 - 228 - 73 - 27 12
Office: Nussallee 15, 1. OG, room 1.012
Address:
University of Bonn
Photogrammetry, IGG
Nussallee 15
53115 Bonn
Google Scholar Profile

Research Interests

  • Motion Planning
  • Collision Avoidance
  • Autonomous Navigation

Short CV

Lorenzo Nardi is a PhD student working in the lab for photogrammetry at the University of Bonn, Germany. He studied artificial intelligence and robotics at Sapienza, University of Rome, Italy. His research mainly focuses on motion planning in the context of mobile robotics. He is interested in autonomous robot navigation and collision avoidance in populated environments.

Projects

  • RobDREAM – Optimising Robot Performance while Dreaming.

Publications

2017

  • L. Nardi and C. Stachniss, “User Preferred Behaviors for Robot Navigation Exploiting Previous Experiences,” in Robotics and Autonomous Systems , 2017. doi:10.1016/j.robot.2017.08.014
    [BibTeX] [PDF]
    Industry demands flexible robots that are able to accomplish different tasks at different locations such as navigation and mobile manipulation. Operators often require mobile robots operating on factory floors to follow definite and predictable behaviors. This becomes particularly important when a robot shares the workspace with other moving entities. In this paper, we present a system for robot navigation that exploits previous experiences to generate predictable behaviors that meet user’s preferences. Preferences are not explicitly formulated but implicitly extracted from robot experiences and automatically considered to plan paths for the successive tasks without requiring experts to hard-code rules or strategies. Our system aims at accomplishing navigation behaviors that follow user’s preferences also to avoid dynamic obstacles. We achieve this by considering a probabilistic approach for modeling uncertain trajectories of the moving entities that share the workspace with the robot. We implemented and thoroughly tested our system both in simulation and on a real mobile robot. The extensive experiments presented in this paper demonstrate that our approach allows a robot for successfully navigating while performing predictable behaviors and meeting user’s preferences

    @InProceedings{nardi17jras,
    Title = {User Preferred Behaviors for Robot Navigation Exploiting Previous Experiences},
    Author = {L. Nardi and C. Stachniss},
    Booktitle = jras,
    Year = {2017},
    Doi = {10.1016/j.robot.2017.08.014},
    Abstract = {Industry demands flexible robots that are able to accomplish different tasks at different locations such as navigation and mobile manipulation. Operators often require mobile robots operating on factory floors to follow definite and predictable behaviors. This becomes particularly important when a robot shares the workspace with other moving entities. In this paper, we present a system for robot navigation that exploits previous experiences to generate predictable behaviors that meet user’s preferences. Preferences are not explicitly formulated but implicitly extracted from robot experiences and automatically considered to plan paths for the successive tasks without requiring experts to hard-code rules or strategies. Our system aims at accomplishing navigation behaviors that follow user’s preferences also to avoid dynamic obstacles. We achieve this by considering a probabilistic approach for modeling uncertain trajectories of the moving entities that share the workspace with the robot. We implemented and thoroughly tested our system both in simulation and on a real mobile robot. The extensive experiments presented in this paper demonstrate that our approach allows a robot for successfully navigating while performing predictable behaviors and meeting user’s preferences},
    Url = {http://www.ipb.uni-bonn.de/pdfs/nardi17jras.pdf}
    }

2016

  • L. Nardi and C. Stachniss, “Experience-Based Path Planning for Mobile Robots Exploiting User Preferences,” in Proceedings of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS) , 2016. doi:10.1109/IROS.2016.7759197
    [BibTeX] [PDF]
    The demand for flexible industrial robotic solutions that are able to accomplish tasks at different locations in a factory is growing more and more. When deploying mobile robots in a factory environment, the predictability and reproducibility of their behaviors become important and are often requested. In this paper, we propose an easy-to-use motion planning scheme that can take into account user preferences for robot navigation. The preferences are extracted implicitly from the previous experiences or from demonstrations and are automatically considered in the subsequent planning steps. This leads to reproducible and thus better to predict navigation behaviors of the robot, without requiring experts to hard-coding control strategies or cost functions within a planner. Our system has been implemented and evaluated on a simulated KUKA mobile robot in different environments.

    @InProceedings{nardi16iros,
    Title = {Experience-Based Path Planning for Mobile Robots Exploiting User Preferences},
    Author = {L. Nardi and C. Stachniss},
    Booktitle = iros,
    Year = {2016},
    Doi = {10.1109/IROS.2016.7759197},
    Abstract = {The demand for flexible industrial robotic solutions that are able to accomplish tasks at different locations in a factory is growing more and more. When deploying mobile robots in a factory environment, the predictability and reproducibility of their behaviors become important and are often requested. In this paper, we propose an easy-to-use motion planning scheme that can take into account user preferences for robot navigation. The preferences are extracted implicitly from the previous experiences or from demonstrations and are automatically considered in the subsequent planning steps. This leads to reproducible and thus better to predict navigation behaviors of the robot, without requiring experts to hard-coding control strategies or cost functions within a planner. Our system has been implemented and evaluated on a simulated KUKA mobile robot in different environments.},
    Url = {http://www.ipb.uni-bonn.de/pdfs/nardi16iros.pdf}
    }

2015

  • F. M. Carlucci, L. Nardi, L. Iocchi, and D. Nardi, “Explicit Representation of Social Norms for Social Robots,” in Proceedings of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS) , 2015, pp. 4191-4196. doi:10.1109/IROS.2015.7353970
    [BibTeX] [PDF]
    As robots are expected to become more and more available in everyday environments, interaction with humans is assuming a central role. Robots working in populated environments are thus expected to demonstrate socially acceptable behaviors and to follow social norms. However, most of the recent works in this field do not address the problem of explicit representation of the social norms and their integration in the reasoning and the execution components of a cognitive robot. In this paper, we address the design of robotic systems that support some social behavior by implementing social norms. We present a framework for planning and execution of social plans, in which social norms are described in a domain and language independent form. A full implementation of the proposed framework is described and tested in a realistic scenario with non-expert and non-recruited users.

    @InProceedings{carlucci15iros,
    Title = {Explicit Representation of Social Norms for Social Robots},
    Author = {F.M. Carlucci and L. Nardi and L. Iocchi and D. Nardi},
    Booktitle = iros,
    Year = {2015},
    Pages = {4191 - 4196},
    Abstract = {As robots are expected to become more and more available in everyday environments, interaction with humans is assuming a central role. Robots working in populated environments are thus expected to demonstrate socially acceptable behaviors and to follow social norms. However, most of the recent works in this field do not address the problem of explicit representation of the social norms and their integration in the reasoning and the execution components of a cognitive robot. In this paper, we address the design of robotic systems that support some social behavior by implementing social norms. We present a framework for planning and execution of social plans, in which social norms are described in a domain and language independent form. A full implementation of the proposed framework is described and tested in a realistic scenario with non-expert and non-recruited users.},
    Doi = {10.1109/IROS.2015.7353970},
    Timestamp = {2016.04.19},
    Url = {http://www.ipb.uni-bonn.de/pdfs/Carlucci2015Explicit.pdf}
    }

igg
Institute of Geodesy
and Geoinformation
lwf
Faculty of Agriculture
ubn
University of Bonn