Publications (by topic)

Explainable planning

  1. 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] [PDF]
  2. 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] [PDF]
  3. M. Brandao, M. Mansouri, A. Mohammed, P. Luff, and A. Coles, “Explainability in Multi-Agent Path/Motion Planning: User-study-driven Taxonomy and Requirements,” in International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2022, pp. 172–180. [Abstract] [PDF]
  4. 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] [PDF]
  5. M. Brandao, G. Canal, S. Krivic, P. Luff, and A. Coles, “How experts explain motion planner output: a preliminary user-study to inform the design of explainable planners,” in IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2021, pp. 299–306. [Abstract] [DOI] [PDF]
  6. R. Eifler, M. Brandao, A. Coles, J. Frank, and J. Hoffman, “Plan-Property Dependencies are Useful: A User Study,” in ICAPS 2021 Workshop on Explainable AI Planning (XAIP), 2021. [Abstract] [PDF]
  7. 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]
  8. 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]

Fairness and ethics in robotics/AI

  1. M. Brandao, M. Mansouri, and M. Magnusson, “Editorial: Responsible Robotics,” Frontiers in Robotics and AI, vol. 9, Jun. 2022. [DOI]
  2. M. Brandao, “Normative roboticists: the visions and values of technical robotics papers,” in IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), 2021, pp. 671–677. [Abstract] [DOI] [PDF]
  3. 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]
  4. J. Grzelak and M. Brandao, “The Dangers of Drowsiness Detection: Differential Performance, Downstream Impact, and Misuses,” in AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES), 2021. [Abstract] [PDF]
  5. M. Brandao, “Fair navigation planning: a humanitarian robot use case,” in KDD 2020 Workshop on Humanitarian Mapping, 2020. [Abstract] [arXiv] [PDF]
  6. M. Brandao, “Discrimination issues in usage-based insurance for traditional and autonomous vehicles,” in Culturally Sustainable Robotics—Proceedings of Robophilosophy 2020, 2020, vol. 335, pp. 395–406. [Abstract] [DOI] [PDF]
  7. 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]
  8. M. Brandao, “Age and gender bias in pedestrian detection algorithms,” in Workshop on Fairness Accountability Transparency and Ethics in Computer Vision, CVPR, 2019. [Abstract] [Dataset] [arXiv] [PDF]
  9. 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]

Hierarchical planning

  1. M. Brandao, A. Coles, A. Coles, and J. Hoffmann, “Merge and Shrink Abstractions for Temporal Planning,” in Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2022. [Abstract] [PDF]
  2. M. Brandao and I. Havoutis, “Learning sequences of approximations for hierarchical motion planning,” in Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2020. [Abstract] [Code] [PDF]

Human-inspired algorithms

  1. Y. M. Shiguematsu, M. Brandao, and A. Takanishi, “Effects of Walking Style and Symmetry on the Performance of Localization Algorithms for a Biped Humanoid Robot,” in 2019 IEEE/SICE International Symposium on System Integration (SII), 2019, pp. 307–312. [Abstract] [DOI] [PDF]
  2. Y. M. Shiguematsu, M. Brandao, K. Hashimoto, and A. Takanishi, “Effects of Biped Humanoid Robot Walking Gaits on Sparse Visual Odometry Algorithms,” in 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), 2018, pp. 160–165. [Abstract] [DOI] [PDF]
  3. M. Brandao, K. Hashimoto, J. Santos-Victor, and A. Takanishi, “Footstep Planning for Slippery and Slanted Terrain Using Human-Inspired Models,” IEEE Transactions on Robotics (TRO), vol. 32, no. 4, pp. 868–879, Aug. 2016. [Abstract] [DOI] [PDF]
  4. M. Brandao, K. Hashimoto, J. Santos-Victor, and A. Takanishi, “Gait planning for biped locomotion on slippery terrain,” in 14th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2014, pp. 303–308. [Abstract] [DOI] [PDF]
  5. L. Jamone, M. Brandao, L. Natale, K. Hashimoto, G. Sandini, and A. Takanishi, “Autonomous online generation of a motor representation of the workspace for intelligent whole-body reaching,” Robotics and Autonomous Systems (RAS), vol. 62, no. 4, pp. 556–567, 2014. [Abstract] [DOI]
  6. M. Brandao, L. Jamone, P. Kryczka, N. Endo, K. Hashimoto, and A. Takanishi, “Reaching for the unreachable: integration of locomotion and whole-body movements for extended visually guided reaching,” in 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2013, pp. 28–33. [Abstract] [DOI] [PDF]

Human-robot interaction

  1. M. Destephe, M. Brandao, T. Kishi, M. Zecca, K. Hashimoto, and A. Takanishi, “Walking in the uncanny valley: importance of the attractiveness on the acceptance of a robot as a working partner,” Frontiers in Psychology, vol. 6, Feb. 2015. [Abstract] [DOI]
  2. M. Destephe, M. Brandao, T. Kishi, M. Zecca, K. Hashimoto, and A. Takanishi, “Emotional Gait: Effects on Humans’ Perception of Humanoid Robots,” in 23rd IEEE International Symposium on Robot and Human Interactive Communication (ROMAN), 2014, pp. 261–266. [Abstract] [DOI]

Legged robots

  1. M. Brandao and I. Havoutis, “Learning sequences of approximations for hierarchical motion planning,” in Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS), 2020. [Abstract] [Code] [PDF]
  2. M. Ramezani, M. Brandao, B. Casseau, I. Havoutis, and M. Fallon, “Legged Robots For Autonomous Inspection And Monitoring Of Offshore Assets,” in Offshore Technology Conference, 2020. [Abstract] [DOI]
  3. M. Brandao, O. B. Aladag, and I. Havoutis, “GaitMesh: controller-aware navigation meshes for long-range legged locomotion planning in multi-layered environments,” IEEE Robotics and Automation Letters (RAL), vol. 5, no. 2, pp. 3596–3603, 2020. [Abstract] [Code] [DOI] [PDF]
  4. M. Brandao, M. Fallon, and I. Havoutis, “Multi-controller multi-objective locomotion planning for legged robots,” in 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2019, pp. 4714–4721. [Abstract] [DOI] [PDF]
  5. Y. M. Shiguematsu, M. Brandao, and A. Takanishi, “Effects of Walking Style and Symmetry on the Performance of Localization Algorithms for a Biped Humanoid Robot,” in 2019 IEEE/SICE International Symposium on System Integration (SII), 2019, pp. 307–312. [Abstract] [DOI] [PDF]
  6. Y. M. Shiguematsu, M. Brandao, K. Hashimoto, and A. Takanishi, “Effects of Biped Humanoid Robot Walking Gaits on Sparse Visual Odometry Algorithms,” in 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids), 2018, pp. 160–165. [Abstract] [DOI] [PDF]
  7. W. X. Tan, M. Brandao, K. Hashimoto, and A. Takanishi, “Trajectory Optimization for High-Power Robots with Motor Temperature Constraints,” in Towards Autonomous Robotic Systems (TAROS), Cham, 2018, pp. 3–14. [Abstract] [DOI] [PDF]
  8. M. Brandao, K. Hashimoto, and A. Takanishi, “Maximize-perturb-minimize: a fast and effective heuristic to obtain sets of locally optimal robot postures,” in IEEE International Conference on Robotics and Biomimetics (ROBIO), 2017. [Abstract] [DOI] [PDF]
  9. M. Brandao, K. Hashimoto, and A. Takanishi, “SGD for robot motion? The effectiveness of stochastic optimization on a new benchmark for biped locomotion tasks,” in 17th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2017. [Abstract] [Code] [Dataset] [arXiv] [DOI] [PDF]
  10. M. Brandao, K. Hashimoto, and A. Takanishi, “Friction from Vision: A Study of Algorithmic and Human Performance with Consequences for Robot Perception and Teleoperation,” in 16th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2016, pp. 428–435. [Abstract] [Dataset] [DOI] [PDF]
  11. M. Brandao, Y. M. Shiguematsu, K. Hashimoto, and A. Takanishi, “Material Recognition CNNs and Hierarchical Planning for Biped Robot Locomotion on Slippery Terrain,” in 16th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2016, pp. 81–88. [Abstract] [Code] [arXiv] [DOI] [PDF]
  12. M. Brandao, K. Hashimoto, J. Santos-Victor, and A. Takanishi, “Footstep Planning for Slippery and Slanted Terrain Using Human-Inspired Models,” IEEE Transactions on Robotics (TRO), vol. 32, no. 4, pp. 868–879, Aug. 2016. [Abstract] [DOI] [PDF]
  13. M. Brandao, K. Hashimoto, and A. Takanishi, “Extending humanoid footstep planning with ZMP tracking error constraints,” in Proceedings of the 6th International Conference on Advanced Mechatronics, 2015, p. 130. [Abstract]
  14. M. Brandao, K. Hashimoto, J. Santos-Victor, and A. Takanishi, “Optimizing energy consumption and preventing slips at the footstep planning level,” in 15th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2015, pp. 1–7. [Abstract] [DOI] [PDF]
  15. M. Brandao, K. Hashimoto, J. Santos-Victor, and A. Takanishi, “Gait planning for biped locomotion on slippery terrain,” in 14th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2014, pp. 303–308. [Abstract] [DOI] [PDF]
  16. M. Brandao, L. Jamone, P. Kryczka, N. Endo, K. Hashimoto, and A. Takanishi, “Reaching for the unreachable: integration of locomotion and whole-body movements for extended visually guided reaching,” in 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2013, pp. 28–33. [Abstract] [DOI] [PDF]

Robot design optimization and calibration

  1. R. P. de Figueiredo, J. le Fevre Sejersen, J. G. Hansen, and M. Brandao, “Integrated design-sense-plan architecture for autonomous geometric-semantic mapping with UAVs,” Frontiers in Robotics and AI, Sep. 2022. [Abstract] [DOI]
  2. R. P. de Figueiredo, J. G. Hansen, J. L. Fevre, M. Brandao, and E. Kayacan, “On the Advantages of Multiple Stereo Vision Camera Designs for Autonomous Drone Navigation,” in ICRA 2021 Workshop on Resilient and Long-Term Autonomy for Aerial Robotic Systems, 2021. [Abstract] [arXiv]
  3. M. Brandao, R. Figueiredo, K. Takagi, A. Bernardino, K. Hashimoto, and A. Takanishi, “Placing and scheduling many depth sensors for wide coverage and efficient mapping in versatile legged robots,” The International Journal of Robotics Research (IJRR), vol. 39, no. 4, pp. 431–460, 2020. [Abstract] [DOI] [PDF]
  4. N. Moutinho et al., “Online calibration of a humanoid robot head from relative encoders, IMU readings and visual data,” in 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2012, pp. 2070–2075. [Abstract] [DOI]

Robot vision

  1. R. P. de Figueiredo, J. le Fevre Sejersen, J. G. Hansen, and M. Brandao, “Integrated design-sense-plan architecture for autonomous geometric-semantic mapping with UAVs,” Frontiers in Robotics and AI, Sep. 2022. [Abstract] [DOI]
  2. R. P. de Figueiredo, J. le Fevre Sejersen, J. G. Hansen, M. Brandao, and E. Kayacan, “Real-Time Volumetric-Semantic Exploration and Mapping: An Uncertainty-Aware Approach,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021. [Abstract] [arXiv]
  3. R. P. de Figueiredo, J. G. Hansen, J. L. Fevre, M. Brandao, and E. Kayacan, “On the Advantages of Multiple Stereo Vision Camera Designs for Autonomous Drone Navigation,” in ICRA 2021 Workshop on Resilient and Long-Term Autonomy for Aerial Robotic Systems, 2021. [Abstract] [arXiv]
  4. M. Brandao, R. Figueiredo, K. Takagi, A. Bernardino, K. Hashimoto, and A. Takanishi, “Placing and scheduling many depth sensors for wide coverage and efficient mapping in versatile legged robots,” The International Journal of Robotics Research (IJRR), vol. 39, no. 4, pp. 431–460, 2020. [Abstract] [DOI] [PDF]
  5. M. Brandao, K. Hashimoto, and A. Takanishi, “Friction from Vision: A Study of Algorithmic and Human Performance with Consequences for Robot Perception and Teleoperation,” in 16th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2016, pp. 428–435. [Abstract] [Dataset] [DOI] [PDF]
  6. M. Brandao, Y. M. Shiguematsu, K. Hashimoto, and A. Takanishi, “Material Recognition CNNs and Hierarchical Planning for Biped Robot Locomotion on Slippery Terrain,” in 16th IEEE-RAS International Conference on Humanoid Robots (Humanoids), 2016, pp. 81–88. [Abstract] [Code] [arXiv] [DOI] [PDF]
  7. M. Brandao, R. Ferreira, K. Hashimoto, A. Takanishi, and J. Santos-Victor, “On Stereo Confidence Measures for Global Methods: Evaluation, New Model and Integration into Occupancy Grids,” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 38, no. 1, pp. 116–128, Jan. 2016. [Abstract] [DOI] [PDF]
  8. M. Brandao, R. Ferreira, K. Hashimoto, J. Santos-Victor, and A. Takanishi, “On the formulation, performance and design choices of Cost-Curve Occupancy Grids for stereo-vision based 3D reconstruction,” in 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2014, pp. 1818–1823. [Abstract] [DOI] [PDF]
  9. M. Brandao, K. Hashimoto, and A. Takanishi, “Uncertainty-based mapping and planning strategies for safe navigation of robots with stereo vision,” in 14th Mechatronics Forum Conference, 2014, pp. 80–85. [Abstract] [PDF]
  10. M. Brandao, R. Ferreira, K. Hashimoto, J. Santos-Victor, and A. Takanishi, “Integrating the whole cost-curve of stereo into occupancy grids,” in 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2013, pp. 4681–4686. [Abstract] [DOI] [PDF]
  11. M. Brandao, R. Ferreira, K. Hashimoto, J. Santos-Victor, and A. Takanishi, “Active Gaze Strategy for Reducing Map Uncertainty along a Path,” in 3rd IFToMM International Symposium on Robotics and Mechatronics, 2013, pp. 455–466. [Abstract] [PDF]
  12. M. Brandao, A. Bernardino, and J. Santos-Victor, “Image Driven Generation of Pose Hypotheses for 3D Model-based Tracking,” in 12th IAPR Conference on Machine Vision Applications (MVA), 2011, pp. 59–62. [Abstract] [PDF]
  13. M. Brandao and A. Bernardino, “Generating pose hypotheses for 3D tracking: a bottom-up approach,” in 16th Portuguese Conference on Pattern Recognition, 2010. [Abstract]