Bruno Lacerda

Senior Researcher in Robotics


Oxford Robotics Institute
University of Oxford
Oxford, United Kingdom

Email: bruno_at_robots.ox.ac.uk

Research

My research focuses on the intersection of decision making under uncertainty, formal methods and mobile robotics. In particular, I am interested on the use of a combination of techniques from learning, planning and model checking to synthesise intelligent, robust and verifiable behaviour, both for single and for multi-robot systems. My research interests include:

  • Sequential Decision Making under Uncertainty
  • Probabilistic Model Checking
  • Planning for Robots
  • Multi-Robot Coordination
  • Autonomy in Extreme Environments
  • Shared Autonomy

My cv (last updated December 2022) can be found here.

Academic Career

Between 2013 and 2017, I was part of the Intelligent Robotics Lab, at the School of Computer Science, University of Birmingham. I mainly worked within the STRANDS (Spatio-Temporal Representations and Activities for Cognitive Control in Long-Term Scenarios) project where I developed control approaches that both handle the inherent uncertainties of human populated environments, and take advantage of the spatio-temporal data obtained from the long term deployment of robot systems to improve their performance.

Education

My academic degrees were awarded by Instituto Superior Técnico, Lisbon, Portugal. My BSc and MSc degrees were obtained on the Department of Mathematics, and my PhD degree was obtained on the Department of Electrical and Computing Engineering. During my PhD, under the supervision of Prof. Pedro Lima, I was a member of the Intelligent Robot and Systems Group in the Institute for Systems and Robotics.

Publications

My Google Scholar Profile is available here.

  • Planning with Hidden Parameter Polynomial MDPs. Clarissa Costen, Marc Rigter, Bruno Lacerda, and Nick Hawes. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023. (bib)

  • Multi-Unit Auctions for Allocating Chance-Constrained Resources. Anna Gautier, Bruno Lacerda, Nick Hawes, and Michael Wooldridge. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023. (bib)

  • Bayesian Reinforcement Learning for Single-Episode Missions in Partially Unknown Environments. Matthew Budd, Paul Duckworth, Nick Hawes, and Bruno Lacerda. In Proceedings of the 2022 Conference on Robot Learning (CoRL), 2022. (bib) (link)

  • Rambo-RL: Robust Adversarial Model-Based Offline Reinforcement Learning. Marc Rigter, Bruno Lacerda, and Nick Hawes. In Proceedings of the 36th Conference on Neural Information Processing Systems (NeurIPS), 2022. (bib)

  • Probabilistic Planning for AUV Data Harvesting from Smart Underwater Sensor Networks. Matthew Budd, Georgios Salavasidis, Izzat Kamarudzaman, Catherine A Harris, Alexander B Phillips, Paul Duckworth, Nick Hawes, and Bruno Lacerda. In Proceedings of the 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022. (bib)

  • Decision-Making under Uncertainty for Multi-Robot Systems. Bruno Lacerda, Anna Gautier, Alex Rutherford, Alex Stephens, Charlie Street, and Nick Hawes. AI Communications, 2022. (bib) (link)

  • Shared Autonomy Systems with Stochastic Operator Models. Clarissa Costen, Marc Rigter, Bruno Lacerda, and Nick Hawes. In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022. (bib) (link)

  • Planning for Risk-Aversion and Expected Value in MDPs. Marc Rigter, Bruno Lacerda, and Nick Hawes. In Proceedings of the 32nd International Conference on Automated Planning and Scheduling (ICAPS), Best Paper Award Runner-Up, 2022. (bib) (link)

  • Time-Bounded Large-Scale Mission Planning Under Uncertainty for UV Disinfection. Lara Brudermüller, Raunak Bhattacharyya, Bruno Lacerda, and Nick Hawes. In ICAPS 2022 Workshop on Planning and Robotics (PlanRob), 2022. (bib) (link)

  • Probabilistic Planning for AUV Data Harvesting from Smart Underwater Sensor Networks. Matthew Budd, Georgios Salavasidis, Izzat Kamarudzaman, Catherine A Harris, Alexander B Phillips, Paul Duckworth, Nick Hawes, and Bruno Lacerda. In ICAPS 2022 Workshop on Planning and Robotics (PlanRob), 2022. (bib)

  • Negotiated Path Planning for Non-Cooperative Multi-Robot Systems. Anna Gautier, Bruno Lacerda, Nick Hawes, and Michael Wooldridge. In Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2022. (bib) (link)

  • Context-Aware Modelling for Multi-Robot Systems Under Uncertainty. Charlie Street, Michal Staniaszek, Manuel Mühlig, Nick Hawes, and Bruno Lacerda. In Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2022. (bib) (link)

  • Proactive Multi-Robot Task Allocation Under Spatiotemporal Uncertainty. Charlie Street, Bruno Lacerda, Manuel Mühlig, and Nick Hawes. In AAMAS 2022 Workshop on Autonomous Robots and Multirobot Systems (ARMS), 2022. (bib)

  • Congestion-Aware Policy Synthesis for Multirobot Systems. Charlie Street, Sebastian Pütz, Manuel Mühlig, Nick Hawes, and Bruno Lacerda. IEEE Transactions on Robotics, 2022. (bib) (link)

  • Risk-Averse Bayes-Adaptive Reinforcement Learning. Marc Rigter, Bruno Lacerda, and Nick Hawes. In Proceedings of the 35th Conference on Neural Information Processing Systems (NeurIPS), 2021. (bib) (link)

  • Risk-Aware Motion Planning in Partially Known Environments. Fernando S. Barbosa, Bruno Lacerda, Paul Duckworth, Jana Tumova, and Nick Hawes. In Proceedings of the 2021 IEEE Conference on Decision and Control (CDC), 2021. (bib) (link)

  • Motion Planning in Uncertain Environments with Rapidly-Exploring Random Markov Decision Processes. Alex Rutherford, Paul Duckworth, Nick Hawes, and Bruno Lacerda. In Proceedings of the 2021 European Conference on Mobile Robots (ECMR), 2021. (bib) (link)

  • Mission Planning in Unknown Environments as Bayesian Reinforcement Learning. Matthew Budd, Paul Duckworth, Nick Hawes, and Bruno Lacerda. In IJCAI 2021 Workshop on Robust and Reliable Autonomy in the Wild, 2021. (bib) (link)

  • Mixed Observability MDPs for Shared Autonomy with Uncertain Human Behaviour. Clarissa Costen, Marc Rigter, Bruno Lacerda, and Nick Hawes. In IJCAI 2021 Workshop on Robust and Reliable Autonomy in the Wild, 2021. (bib) (link)

  • Active Inference for Integrated State-Estimation, Control, and Learning. Mohamed Baioumy, Paul Duckworth, Bruno Lacerda and Nick Hawes. In Proceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021. (bib) (link)

  • Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes. Marc Rigter, Bruno Lacerda, and Nick Hawes. In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI), 2021. (bib) (link)

  • Negotiated Path Planning for Non-Cooperative Multi-Robot Systems. Anna Gautier, Bruno Lacerda, Nick Hawes, and Michael Wooldridge. In IJCAI 2020 Workshop on Multi-Agent Path Finding, 2020. (bib) (link)

  • Time-Bounded Mission Planning in Time-Varying Domains with Semi-MDPs and Gaussian Processes. Paul Duckworth, Bruno Lacerda, and Nick Hawes. In Proceedings of the 2020 Conference on Robot Learning (CoRL), 2020. (bib) (link)

  • Battery Charge Scheduling in Long-Life Autonomous Mobile Robots via Multi-Objective Decision Making under Uncertainty. Milan Tomy, Bruno Lacerda, Nick Hawes and Jeremy Wyatt. Robotics and Autonomous Systems, Vol. 133, 2020. (bib) (link)

  • Markov Decision Processes with Unknown State Feature Values for Safe Exploration using Gaussian Processes. Matthew Budd, Bruno Lacerda, Paul Duckworth, Andrew West, Barry Lennox, and Nick Hawes. In Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020. (bib) (link)

  • Long-Run Multi-Robot Planning under Uncertain Action Durations for Persistent Tasks. Carlos Azevedo, Bruno Lacerda, Nick Hawes, and Pedro U. Lima. In Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020. (bib) (link)

  • Adaptive Manipulator Control using Active Inference with Precision Learning. Mohamed Baioumy, Matias Mattamala, Paul Duckworth, Bruno Lacerda, and Nick Hawes. In Proceedings of the 3rd UK-RAS Conference for PhD Students & Early-Career Researchers (UKRAS), 2020. (bib) (link)

  • A Framework for Learning from Demonstration with Minimal Human Effort. Marc Rigter, Bruno Lacerda, and Nick Hawes. Robotics and Automation Letters, Vol. 5, Issue 2, 2020. (bib) (link)

  • Convex Hull Monte-Carlo Tree Search. Michael Painter, Bruno Lacerda, and Nick Hawes. In Proceedings of the 30th International Conference on Automated Planning and Scheduling (ICAPS), 2020. (bib) (link)

  • Multi-Robot Planning Under Uncertainty with Congestion-Aware Models. Charlie Street, Bruno Lacerda, Manuel Mühlig, and Nick Hawes. In Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2020. (bib) (link)

  • Long-Run Multi-Robot Planning With Uncertain Task Durations. Carlos Azevedo, Bruno Lacerda, Nick Hawes, and Pedro U. Lima. In Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2020. (bib) (link)

  • Petri Net Based Multi-Robot Task Coordination from Temporal Logic Specifications. Bruno Lacerda and Pedro U. Lima. Robotics and Autonomous Systems, Vol. 122, 2019. (bib) (link)

  • Battery Charge Scheduling in Long-Life Autonomous Mobile Robots. Milan Tomy, Bruno Lacerda, Nick Hawes and Jeremy Wyatt. In Proceedings of the 2019 European Conference on Mobile Robots (ECMR), Prague, Czech Republic, 2019. (bib) (link)

  • Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints. Masoumeh Mansouri, Bruno Lacerda, Nick Hawes and Federico Pecora. In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI), Macau, China, 2019. (bib) (link)

  • Multi-Robot Planning Under Uncertain Travel Times and Safety Constraints. Masoumeh Mansouri, Bruno Lacerda, Nick Hawes and Federico Pecora. In ICRA 2019 Workshop on Resilient Robot Teams: Composing, Acting, and Learning, Montreal, Canada, 2019. (bib) (link)

  • Probabilistic Planning with Formal Performance Guarantees for Mobile Service Robots. Bruno Lacerda, Fatma Faruq, David Parker and Nick Hawes. International Journal of Robotics Research, Vol. 38, No. 9, 2019. (bib) (link) (video)

  • Simultaneous Task Allocation and Planning Under Uncertainty. Fatma Faruq, Bruno Lacerda, Nick Hawes and David Parker. In Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 2018. (bib) (link)

  • Policy Generation with Probabilistic Guarantees for Long-term Autonomy of a Mobile Robot (Demo). Bruno Lacerda, David Parker and Nick Hawes. In FLoC 2018 Workshop on the Verification and Validation of Autonomous Systems (VaVAS), Oxford, United Kingdom, 2018. (bib) (link)

  • Multi-Objective Policy Generation for Mobile Robots Under Probabilistic Time-Bounded Guarantees. Bruno Lacerda, David Parker and Nick Hawes. In Proceedings of the 27th International Conference on Automated Planning and Scheduling (ICAPS), Pittsburgh, PA, USA, 2017. (bib) (link)

  • The STRANDS Project: Long-Term Autonomy in Everyday Environments. Nick Hawes et al. IEEE Robotics and Automation Magazine, Vol. 24, Issue 3, 2017. (bib) (link)

  • Partial Order Temporal Plan Merging for Mobile Robot Tasks. Lenka Mudrova, Bruno Lacerda and Nick Hawes. In Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI), The Hague, Netherlands, 2016. (bib) (link)

  • Nested Value Iteration for Partially Satisfiable Co-Safe LTL Specifications (Extended Abstract). Bruno Lacerda, David Parker and Nick Hawes. In AAAI Fall Symposium on Sequential Decision Making for Intelligent Agents (SDMIA), Arlington, Virginia, USA, 2015. (bib) (link)

  • An Integrated Control Framework for Long-Term Autonomy in Mobile Service Robots. Lenka Mudrova, Bruno Lacerda and Nick Hawes. In Proceedings of the 7th European Conference on Mobile Robots (ECMR), Lincoln, UK, 2015. (bib) (link)

  • Optimal Policy Generation for Partially Satisfiable Co-Safe LTL Specifications. Bruno Lacerda, David Parker and Nick Hawes. In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, 2015. (bib) (pdf)

  • Now or later? Predicting and maximising success of navigation actions from long-term experience. Jaime P. Fentanes, Bruno Lacerda, Tomas Krajnik, Nick Hawes and Marc Hanheide. In Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015. (bib) (link)

  • Optimal and dynamic planning for Markov decision processes with co-safe LTL specifications. Bruno Lacerda, David Parker and Nick Hawes. In Proceedings of the 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Chicago, IL, USA, 2014. (bib) (link)

  • Optimal Motion Planning for Markov Decision Processes with Co-Safe Linear Temporal Logic Specifications. Bruno Lacerda, David Parker and Nick Hawes. In 31st Workshop of the UK Planning & Scheduling Special Interest Group (PlanSIG), Edinburgh, UK, 2014. (bib) (link)

  • On the Notion of Uncontrollable Marking in Supervisory Control of Petri Nets. Bruno Lacerda and Pedro U. Lima. IEEE Transactions on Automatic Control, Vol. 59, No. 11, 2014. (bib) (link)

  • LTL-Based Decentralized Supervisory Control of Multi-Robot Tasks Modelled as Petri Nets. Bruno Lacerda and Pedro U. Lima. In Proceedings of the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), San Francisco, CA, USA, 2011. (bib) (link)

  • Designing Petri Net Supervisors from LTL Specifications. Bruno Lacerda and Pedro U. Lima. In Proceedings of Robotics: Science and Systems VII (RSS), Los Angeles, CA, USA, 2011. (bib) (link) (video)

  • Designing Petri Net Supervisors for Multi-Agent Systems from LTL Specifications (Extended Abstract). Bruno Lacerda and Pedro U. Lima. In Proceedings of the 10th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), Taipei, Taiwan, 2011. (bib) (link)

  • Petri Net Based Supervisory Control of a Social Robot with LTL Specifications. Bruno Lacerda, Pedro U. Lima, Javi Gorostiza and Miguel A. Salichs. In Proceedings of the 11th International Conference On Mobile Robots And Competitions, Lisbon, Portugal, 2011. (bib) (pdf) (video)

  • Petri Nets as an Analysis Tool for Data Flow in Wireless Sensor Networks. Bruno Lacerda and Pedro U. Lima. In Proceedings of the 1st Portuguese Conference on Wireless Sensor Networks (CNRS), Coimbra, Portugal, 2011. (bib) (pdf)

  • LTL Plan Specification for Robotic Tasks Modelled as Finite State Automata. Bruno Lacerda and Pedro U. Lima. In AAMAS 2009 Workshop on Agent Design: Advancing from Practice to Theory (ADAPT), Budapest, Hungary, 2009. (bib) (pdf)

  • Linear-Time Temporal Logic Control of Discrete Event Models of Cooperative Robots. Bruno Lacerda and Pedro U. Lima. Journal of Physical Agents, Vol. 2, No. 1, 2008. (bib) (link)

Theses

  • Supervision of Discrete Event Systems Based on Temporal Logic Specifications. Bruno Lacerda. PhD Thesis, Instituto Superior Técnico, 2013. (bib) (link)

  • Linear-Time Temporal Logic Control of Discrete Event Systems. Bruno Lacerda. MSc Thesis, Instituto Superior Técnico, 2007. (bib) (link)