Ermano Arruda
exa371 at bham dot ac dot uk

I am a PhD student in Computer Science at the University of Birmingham. I am supervised by Prof. Jeremy Wyatt and Dr. Marek Kopicki. I am also a member of the Intelligent Robotics Lab, in which my research focus is machine learning for robotic perception in manipulation tasks.

I have worked on active vision for robotic grasping in the PaCMan project .

Before being a postgraduate student, I received a Bachelors in Computer Science at the Center for Informatics, Federal University of Pernambuco. I have also been part of the VoxarLabs , where I worked on computer vision, augmented and virtual reality research and applications.

CV  /  Google Scholar  /  GitHub  /  LinkedIn

Research

I am interested in how closing the loop between perception and action can improve performance in manipulation tasks for robotics. My research focus is robot perception, machine learning and control.

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Active vision for dexterous grasping of novel objects
Ermano Arruda, Jeremy Wyatt, Marek Kopicki
International Conference on Intelligent Robots and Systems (IROS), 2016
video / bibtex

We tackled the problem of improving robot grasp performance using active vision. We sought to increase grasping success via two view selection heuristics: one that would allow the robot to explore good quality grasp contact points, and another that would permit the robot to investigate its workspace to make sure candidate grasp trajectories would not lead to collisions with unseen parts of the object to be grasped. Our results showed that this approach yielded better grasp success rate when compared to a random view selection strategy, while using fewer camera views for grasp planning.

Course Projects
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A study on SLAM techniques with applications on robot perception
Ermano Arruda, Veronica Teichrieb, Joao Paulo Lima, 2015
video


In my final year project I have implemented a Graph SLAM (Simultaneous Localisation and Mapping) system for mobile robots. The system was quantitavely evaluated on the TUM RGB-D SLAM Benchmark dataset. The final system was able to successfully map a whole flat using FAB-MAP for loop-closure detection.

Awards
pacman

  • First place at ISMAR Off-site Tracking Competition, Fukuoka, Japan, 2015. Developed a monocular visual odometry system with additional sparse bundle adjustment for camera trajectory optimisation.
  • video1 / video2

    code

pacman

  • Winning team CESAR-VoxarLabs at LARC/CBR - Latin American and Brazilian Robotics Competition, RoboCup@Home, 2014. Worked on object-tracking and detection system.
  • meet i-zak

Teaching
teach

06-28912: Graphics
Teaching Assistant (TA)

06-27821: Software Workshop 1
Teaching Assistant (TA)


This webpage is really nice.


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