TY - GEN
T1 - Model-based robotic hand tracking and gripper state determination
AU - Araujo, Arthur Cruzde
AU - Lima, Antonio Marcus Nogueira
AU - Mattila, Jaakko Mikael
AU - Muthusamy, Rajkumar
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/15
Y1 - 2017/12/15
N2 - This paper proposes a 3D model-based vision system for detecting a manipulator's gripper on a scene, tracking it as it moves and continuously determining its state (opened or closed), information that is used to signal that an object can be grasped. Build upon the Robot Operating System (ROS), it mainly comprises a registration pipeline, a tracking algorithm and a state classifier based on a proposed measure of similarity between point clouds. The test platform includes a robotic arm and a depth camera. Satisfactory experimental results were obtained: tracking had a good performance for well-behaved trajectories and the detection of not only the state of the gripper, showing robustness to self-occlusion, but also the presence of an object, were successful. The state detector produced relevant output on grasping of unknown objects to be used in future works, which might contemplate the insertion of this system in a multi-robot collaborative scenario. The test results presented in this paper demonstrate the correctness of the proposed methodology and the feasibility of the proposed system design.
AB - This paper proposes a 3D model-based vision system for detecting a manipulator's gripper on a scene, tracking it as it moves and continuously determining its state (opened or closed), information that is used to signal that an object can be grasped. Build upon the Robot Operating System (ROS), it mainly comprises a registration pipeline, a tracking algorithm and a state classifier based on a proposed measure of similarity between point clouds. The test platform includes a robotic arm and a depth camera. Satisfactory experimental results were obtained: tracking had a good performance for well-behaved trajectories and the detection of not only the state of the gripper, showing robustness to self-occlusion, but also the presence of an object, were successful. The state detector produced relevant output on grasping of unknown objects to be used in future works, which might contemplate the insertion of this system in a multi-robot collaborative scenario. The test results presented in this paper demonstrate the correctness of the proposed methodology and the feasibility of the proposed system design.
KW - CAD-based vision
KW - ROS
KW - model-based
KW - registration
KW - robotic manipulators
KW - tracking
UR - http://www.scopus.com/inward/record.url?scp=85048533891&partnerID=8YFLogxK
U2 - 10.1109/SBR-LARS-R.2017.8215330
DO - 10.1109/SBR-LARS-R.2017.8215330
M3 - Conference contribution
AN - SCOPUS:85048533891
T3 - Proceedings - 2017 LARS 14th Latin American Robotics Symposium and 2017 5th SBR Brazilian Symposium on Robotics, LARS-SBR 2017 - Part of the Robotics Conference 2017
SP - 1
EP - 6
BT - Proceedings - 2017 LARS 14th Latin American Robotics Symposium and 2017 5th SBR Brazilian Symposium on Robotics, LARS-SBR 2017 - Part of the Robotics Conference 2017
A2 - Tonidandel, Flavio
A2 - Todt, Eduardo
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th Latin American Robotics Symposium and 5th Brazilian Symposium on Robotics, LARS-SBR 2017
Y2 - 8 November 2017 through 10 November 2017
ER -