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Robotics and Biology LaboratoryRoberto Martín-Martín

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Roberto Martín-Martín

Lupe

Email: roberto.martinmartin(at)tu-berlin.de

Room: MAR 5.065
Telephone: +49.30.314-73118
Office Hours: on request

Research

In a (near) future I would like to see robots assisting and working autonomously in human environments. However, these environments are highly unpredictable and dynamic. My research interest is to provide robots with the necessary perceptual skills to understand and successfully manipulate these unstructured environments. I believe that the key to a successful understanding of the environment should include three factors: interaction with the world, continuous probabilistic (bayesian) estimation and learning and multimodal perception. By correctly combining these factors the robot can crack the complexity and variety of human environments.

My recent work applies these ideas to the robust perception of degrees of freedom in unstructured environments from interactions. This knowledge is crucial for robots interacting in our homes. Doors, drawers, or scissors are some examples of articulated objects with degrees of freedom that the robot would need to perceive and understand in order to successfully and purposely manipulate them.

Research interests: 

  • Active and Interactive Perception
  • Sensorimotor Contingencies
  • Bayesian State Estimation and Bayesian Exploration
  • Multimodal Perception and Control
  • Machine Learning

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Vita

Publications

Roberto Martín-Martín and Oliver Brock. Cross-Modal Interpretation of Multi-Modal Sensor Streams in Interactive Perception Based on Coupled Recursion. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (in press), 2017.

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Roberto Martín-Martín and Oliver Brock. Building Kinematic and Dynamic Models of Articulated Objects with Multi-Modal Interactive Perception. AAAI Symposium on Interactive Multi-Sensory Object Perception for Embodied Agents, 2017.

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Clemens Eppner and Roberto Martín-Martín and Oliver Brock. Physics-Based Selection of Actions That Maximize Motion for Interactive Perception. RSS workshop: Revisiting Contact - Turning a problem into a solution, 2017.

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Rico Jonschkowski and Clemens Eppner and Sebastian Höfer and Roberto Martín-Martín and Oliver Brock. Probabilistic Multi-Class Segmentation for the Amazon Picking Challenge. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016.

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Roberto Martín-Martín and Arne Sieverling and Oliver Brock. Estimating the Relation of Perception and Action During Interaction. International Workshop on Robotics in the 21st century: Challenges and Promises, 2016.

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Clemens Eppner and Sebastian Höfer and Rico Jonschkowski and Roberto Martín-Martín and Arne Sieverling and Vincent Wall and Oliver Brock. Lessons from the Amazon Picking Challenge: Four Aspects of Building Robotic Systems. Proceedings of Robotics: Science and Systems, 2016.

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Roberto Martín-Martín and Sebastian Höfer and Oliver Brock. An Integrated Approach to Visual Perception of Articulated Objects. Proceedings of the IEEE International Conference on Robotics and Automation, pp. 5091 - 5097, 2016.

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Roberto Martín-Martín and Oliver Brock. Online Interactive Perception of Articulated Objects with Multi-Level Recursive Estimation Based on Task-Specific Priors. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2494-2501, 2014.

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Roberto Martín-Martín and Oliver Brock. Deterioration of Depth Measurements due to Interference of Multiple RGB-D Sensors. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4205-4212, 2014.

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Dragoljub Surdilovic and Yelve Yakut and T-M. Nguyen and X. B. Pham and Axel Vick and Roberto Martín-Martín. Compliance Control with Dual-Arm Humanoid Robots: Design, Planning and Programming. Proceedings of the International Conference on Humanoid Robots, pp. 275-281, 2010.

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