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About

I'm a fast learner software engineer, always looking to expand my knowledge in new technologies and with great interest in science (computer science and engineering, robotics, biotechnology, space exploration, among others).

My main research areas are augmented reality, 3D perception, computer vision, safety critical systems, assembly automation, localization and mapping of autonomous vehicles among many others within the industrial and mobile robotics fields.

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Publications

2021

Reconfigurable Grasp Planning Pipeline with Grasp Synthesis and Selection Applied to Picking Operations in Aerospace Factories

Authors
de Souza, JPC; Costa, CM; Rocha, LF; Arrais, R; Moreira, AP; Pires, EJS; Boaventura Cunha, J;

Publication
Robotics and Computer-Integrated Manufacturing

Abstract

2021

Force control heuristics for surpassing pose uncertainty in mobile robotic assembly platforms

Authors
Moutinho, D; Rebelo, P; Costa, C; Rocha, L; Veiga, G;

Publication
2021 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

Abstract

2021

On the development of a collaborative robotic system for industrial coating cells

Authors
Arrais, R; Costa, CM; Ribeiro, P; Rocha, LF; Silva, M; Veiga, G;

Publication
The International Journal of Advanced Manufacturing Technology

Abstract

2020

Perception of Entangled Tubes for Automated Bin Picking

Authors
Leao, G; Costa, CM; Sousa, A; Veiga, G;

Publication
Robot 2019: Fourth Iberian Robotics Conference - Advances in Robotics, Volume 1, Porto, Portugal, 20-22 November, 2019.

Abstract

2020

Detecting and Solving Tube Entanglement in Bin Picking Operations

Authors
Leao, G; Costa, CM; Sousa, A; Veiga, G;

Publication
Applied Sciences

Abstract
Manufacturing and production industries are increasingly turning to robots to carry out repetitive picking operations in an efficient manner. This paper focuses on tackling the novel challenge of automating the bin picking process for entangled objects, for which there is very little research. The chosen case study are sets of freely curved tubes, which are prone to occlusions and entanglement. The proposed algorithm builds a representation of the tubes as an ordered list of cylinders and joints using a point cloud acquired by a 3D scanner. This representation enables the detection of occlusions in the tubes. The solution also performs grasp planning and motion planning, by evaluating post-grasp trajectories via simulation using Gazebo and the ODE physics engine. A force/torque sensor is used to determine how many items were picked by a robot gripper and in which direction it should rotate to solve cases of entanglement. Real-life experiments with sets of PVC tubes and rubber radiator hoses showed that the robot was able to pick a single tube on the first try with success rates of 99% and 93%, respectively. This study indicates that using simulation for motion planning is a promising solution to deal with entangled objects.