1. |
- Aderklou, Christina, et al.
(författare)
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Pedatronics : Robotic toys as a source to evoke young girls’ technological interest
- 2002
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Ingår i: 32nd Annual Frontiers in Education. Leading a Revolution in Engineering and Computer Science Education. - San Diego : Institute of Electrical and Electronics Engineers (IEEE). - 0780374444 ; , s. F1C-19-F1C-24
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Konferensbidrag (refereegranskat)abstract
- This paper presents some results within Pedatronics; a fusion between pedagogics and mechatronics. Our research interest is to study what emerges in the play with robotic toys. Field-experimental studies of 67 year old children’s purposeless play with robotic toys created a self-developmental sphere, as well as evoked young girl’s technological interest. Both girls and boys prolonged and intensified their interest according to the amount of gadgets involved. The results disclose a learning potential, indicating the importance to develop strategies at an early stage in order to encourage girls to choose technological and engineering educations. The study recommend engineers and toy designers, in cooperation with children, to move towards ’Integrated Play Systems’. Due to an ethological method, the results differ from other studies of children’s play with technological advanced artefacts. © 2002 IEEE
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2. |
- Antonelo, Eric Aislan, et al.
(författare)
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Intelligent autonomous navigation for mobile robots : Spatial concept acquisition and object discrimination
- 2005
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Ingår i: 2005 IEEE International Symposium on Computational Intelligence in Robotics and Automation, Proceedings. - New York : IEEE Press. - 0780393554 ; , s. 553-557
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Konferensbidrag (refereegranskat)abstract
- An autonomous system able to construct its own navigation strategy for mobile robots is proposed. The navigation strategy is molded from navigation experiences (succeeding as the robot navigates) according to a classical reinforcement learning procedure. The autonomous system is based on modular hierarchical neural networks. Initially the navigation performance is poor (many collisions occur). Computer simulations show that after a period of learning the autonomous system generates efficient obstacle avoidance and target seeking behaviors. Experiments also offer support for concluding that the autonomous system develops a variety of object discrimination capability and of spatial concepts.
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3. |
- Antonelo, Eric A., et al.
(författare)
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Modular Neural Network and Classical Reinforcement Learning for Autonomous Robot Navigation : Inhibiting Undesirable Behaviors
- 2006
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Ingår i: International Joint Conference on Neural Networks, 2006. IJCNN '06. - Piscataway, N.J. : IEEE Press. - 0780394909 ; , s. 498-505
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Konferensbidrag (refereegranskat)abstract
- Classical reinforcement learning mechanisms and a modular neural network are unified for conceiving an intelligent autonomous system for mobile robot navigation. The conception aims at inhibiting two common navigation deficiencies: generation of unsuitable cyclic trajectories and ineffectiveness in risky configurations. Distinct design apparatuses are considered for tackling these navigation difficulties, for instance: 1) neuron parameter for memorizing neuron activities (also functioning as a learning factor), 2) reinforcement learning mechanisms for adjusting neuron parameters (not only synapse weights), and 3) a inner-triggered reinforcement. Simulation results show that the proposed system circumvents difficulties caused by specific environment configurations, improving the relation between collisions and captures.
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4. |
- Baerveldt, Albert-Jan, et al.
(författare)
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A low-cost and low-weight attitude estimation system for an autonomous helicopter
- 1997
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Ingår i: IEEE International Conference on Intelligent Engineering Systems, Proceedings, INES. - Piscataway, N.J. : IEEE Press. - 0780336275 ; , s. 391-395
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In this paper a low-cost and low-weight attitude estimation system for an autonomous helicopter is presented. The system is based on an inclinometer and a rate gyro. The data coming from the sensors is fused through a complementary filter. In this way the slow dynamics of the inclinometer can be effectively compensated. Tests have shown that we obtained a very effective attitude estimation system.
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5. |
- Baerveldt, Albert-Jan, et al.
(författare)
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A low-cost colour vision-system for robot design competitions
- 1998
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Ingår i: Mechatronics '98. - Oxford : Pergamon Press. - 0080433391 ; , s. 595-600
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Konferensbidrag (refereegranskat)abstract
- In this paper we present a low-cost colour vision system mainly intended for robot design competitions, which nowadays is a popular, project-oriented, way of teaching mechatronics in engineering curriculums. The estimated cost is about 450 dollar inclusive colour camera and the system is small enough to be carried on-board relative small mobile robots. The system is build around a signal processor TMS C31. We also present and discuss the experiences made with the system in our robot design competition.
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6. |
- Baerveldt, Albert-Jan
(författare)
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A vision system for object verification and localization based on local features
- 2001
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Ingår i: Robotics and Autonomous Systems. - Amsterdam : Elsevier. - 0921-8890 .- 1872-793X. ; 34:2-3, s. 83-92
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Tidskriftsartikel (refereegranskat)abstract
- An object verification and localization system should answer the question whether an expected object is present in an image or not, i.e. verification, and if present where it is located. Such a system would be very useful for mobile robots, e.g. for landmark recognition or for the fulfilment of certain tasks. In this paper, we present an object verification and localization system specially adapted to the needs of mobile robots. The object model is based on a collection of local features derived from a small neighbourhood around automatically detected interest points. The learned representation of the object is then matched with the image under consideration. The tests, based on 81 images, showed a very satisfying tolerance to scale changes of up to 50%, to viewpoint variations of 20, to occlusion of up to 80% and to major background changes as well as to local and global illumination changes. The tests also showed that the verification capabilities are very good and that similar objects did not trigger any false verification.
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7. |
- Baerveldt, Albert-Jan, et al.
(författare)
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Editorial
- 2003
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Ingår i: Robotics and Autonomous Systems. - Amsterdam : Elsevier. - 0921-8890 .- 1872-793X. ; 44:1, s. 1-
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Tidskriftsartikel (populärvet., debatt m.m.)
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8. |
- Baerveldt, Albert-Jan
(författare)
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Guest editorial : Agricultural robotics
- 2002
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Ingår i: Autonomous Robots. - Berlin : Springer. - 0929-5593 .- 1573-7527. ; 13:1, s. 5-7
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Tidskriftsartikel (refereegranskat)
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9. |
- Baerveldt, Albert-Jan, et al.
(författare)
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Vision-guided mobile robots for design competitions
- 2003
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Ingår i: IEEE robotics & automation magazine. - : IEEE, The Institute of Electrical and Electronics Engineers. - 1070-9932 .- 1558-223X. ; 10:2, s. 38-44
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Tidskriftsartikel (refereegranskat)abstract
- The use of popular and effective robot-design competitions in teaching system integration in engineering curricula was discussed. Such robot competitions give students open-ended problem spaces, teaches them to work in groups and stimulates creativity. The technical and pedagogical aspects of robot competitions along with their experiences and shortcomings were also discussed.
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10. |
- Baerveldt, Albert-Jan, et al.
(författare)
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Visual guidance of mobile robots using a neural network
- 1998
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Ingår i: Mechatronics '98. - Oxford : Pergamon Press. - 0080433391 ; , s. 427-431
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Konferensbidrag (refereegranskat)abstract
- In this paper we present a self-learning method for low-level navigation for autonomous mobile robots, based on a neural network. Both corridor following and obstacle avoidance in indoor environments are successfully managed by the same network. Raw gray scale images of size 32 by 23 pixels are processed one by one by a feed forward neural network. The output signals of the network represent the appropriate steering actions of the robot.
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