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We design new algorithms and datasets that mitigate risks and promote positive social impact.

Relevant publications

  1. Q. Liu and M. Brandao, “Generating Environment-based Explanations of Motion Planner Failure: Evolutionary and Joint-Optimization Algorithms,” in 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024. [Abstract] [PDF] #transparency
  2. K. Alsheeb and M. Brandao, “Towards Explainable Road Navigation Systems,” in IEEE International Conference on Intelligent Transportation Systems (ITSC), 2023. [Abstract] [Code] [PDF] #transparency
  3. Z. Zhou and M. Brandao, “Noise and Environmental Justice in Drone Fleet Delivery Paths: A Simulation-Based Audit and Algorithm for Fairer Impact Distribution,” in 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023. [Abstract] [Code] [PDF] #fairness #wellbeing
  4. M. E. Akintunde, M. Brandao, G. Jahangirova, H. Menendez, M. R. Mousavi, and J. Zhang, “On Testing Ethical Autonomous Decision-Making,” in Springer LNCS Festschrift dedicated to Jan Peleska’s 65th Birthday, 2023. #fairness
  5. R. Eifler, M. Brandao, A. Coles, J. Frank, and J. Hoffman, “Evaluating Plan-Property Dependencies: A Web-Based Platform and User Study,” in Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2022. [Abstract] [DOI] [PDF] #transparency
  6. M. Brandao and Y. Setiawan, “’Why Not This MAPF Plan Instead?’ Contrastive Map-based Explanations for Optimal MAPF,” in ICAPS 2022 Workshop on Explainable AI Planning (XAIP), 2022. [Abstract] [Code] [PDF] #transparency
  7. M. Brandao, A. Coles, and D. Magazzeni, “Explaining Path Plan Optimality: Fast Explanation Methods for Navigation Meshes Using Full and Incremental Inverse Optimization,” in Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2021, pp. 56–64. [Abstract] [Code] [DOI] [PDF] #transparency
  8. M. Brandao, G. Canal, S. Krivic, and D. Magazzeni, “Towards providing explanations for robot motion planning,” in 2021 IEEE International Conference on Robotics and Automation (ICRA), 2021, pp. 3927–3933. [Abstract] [DOI] [PDF] #transparency
  9. M. Brandao, “Socially Fair Coverage: The Fairness Problem in Coverage Planning and a New Anytime-Fair Method,” in 2021 IEEE International Conference on Advanced Robotics and its Social Impacts (ARSO), 2021, pp. 227–233. [Abstract] [DOI] [PDF] #fairness
  10. M. Brandao and D. Magazzeni, “Explaining plans at scale: scalable path planning explanations in navigation meshes using inverse optimization,” in IJCAI 2020 Workshop on Explainable Artificial Intelligence (XAI), 2020. [Abstract] [PDF] #transparency
  11. M. Brandao, “Fair navigation planning: a humanitarian robot use case,” in KDD 2020 Workshop on Humanitarian Mapping, 2020. [Abstract] [arXiv] [PDF] #fairness
  12. M. Brandao, M. Jirotka, H. Webb, and P. Luff, “Fair navigation planning: a resource for characterizing and designing fairness in mobile robots,” Artificial Intelligence (AIJ), vol. 282, 2020. [Abstract] [DOI] [PDF] #fairness
  13. M. Brandao, “Moral Autonomy and Equality of Opportunity for Algorithms in Autonomous Vehicles,” in Envisioning Robots in Society: Power, Politics, and Public Space—Proceedings of Robophilosophy 2018, 2018, vol. 311, pp. 302–310. [Abstract] [DOI] [PDF] #fairness