关键词： Reinforcement learning   Spiking neural networks   Mobile robot   Thalamo-cortico-thalamic circuitry   Dopamine modulator  

摘要： In this paper, the behavioral learning of robots through spiking neural networks is studied in which the architecture of the network is based on the thalamo-cortico-thalamic circuitry of the mammalian brain. According to a variety of neurons, the Izhikevich model of single neuron is used for the representation of neuronal behaviors. One thousand and ninety spiking neurons are considered in the network. The spiking model of the proposed architecture is derived and prepared for the learning problem of robots. The reinforcement learning algorithm is based on spike-timing-dependent plasticity and dopamine release as a reward. It results in strengthening the synaptic weights of the neurons that are involved in the robot's proper performance. Sensory and motor neurons are placed in the thalamus and cortical module, respectively. The inputs of thalamo-cortico-thalamic circuitry are the signals related to distance of the target from robot, and the outputs are the velocities of actuators. The target attraction task is used as an example to validate the proposed method in which dopamine is released when the robot catches the target. Some simulation studies, as well as experimental implementation, are done on a mobile robot named Tabrizbot. Experimental studies illustrate that after successful learning, the meantime of catching target is decreased by about 36%. These prove that through the proposed method, thalamo-cortical structure could be trained successfully to learn to perform various robotic tasks.

关键词： artificial intelligence (AI)   robotics   analytical framework   learning designs   learning outcomes   learning trajectories  

摘要： This qualitative study examines the use of artificial intelligence (AI) and robotics in learning designs from the perspective of learning sciences. The literature on the topic indicates that there is not enough research on including diverse learning outcomes in the designs for learning. Therefore, the purpose of this study was to understand how AI and robots impact physical, social-emotional and intellectual learning outcomes through the implementation of learning designs that are guided by selected design principles. In this study, the design-based research (DBR) methodology was employed for investigating learning in naturalistic contexts. The intervention was implemented in a primary school in which learners used educational robots. The main findings reveal that the development of an integrated analytical framework, which considers a broader spectrum of human potential, allows for analyzing students' learning outcomes in a more integral, inclusive and balanced way. This, in turn, promotes students' learning by using AI and robots. Another finding reveals that the impact of using AI and robotics on learning designs is reflected in learners' personal trajectories having different pathways and paces. Finally, the lessons learned and the challenges to be overcome are summarized, and recommendations are made for future research for the enhancement of learning experiences that use AI and robotics.

关键词： Topological mapping   Illumination invariance   Community detection   Robot localization  

摘要： Due to its vast applicability, the semantic interpretation of regions or entities increasingly attracts the attention of scholars within the robotics community. The paper at hand introduces a novel unsupervised technique to semantically identify the position of an autonomous agent in unknown environments. When the robot explores a certain path for the first time, community detection is achieved through graph-based segmentation. This allows the agent to semantically define its surroundings in future traverses even if the environment's lighting conditions are changed. The proposed semantic clustering technique exploits the Louvain community detection algorithm, which constitutes a novel and efficient method for identifying groups of measurements with consistent similarity. The produced communities are combined with metric information, as provided by the robot's odometry through a hierarchical agglomerative clustering method. The suggested algorithm is evaluated in indoors and outdoors datasets creating topological maps capable of assisting semantic localization. We demonstrate that the system categorizes the places correctly when the robot revisits an environment despite the possible lighting variation. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Space debris  

摘要： With the number of large-scale facilities, malfunctioning spacecraft, and debris expected to increase in space, on-orbit servicing, including assembly, monitoring, maintenance, refueling and deorbiting, has become a major concern in space missions. Space robots can efficiently cope with a large number of on-orbit servicing missions while avoiding the high risks and reducing costs of extravehicular activity. The challenges of space robots with multiple arms include the complex dynamics and the coupling between the floating base and the end-effector. To handle these problems, a dynamics model with topological structure is firstly established for a four-arm space robot based on the kinematic chain symbolic calculus system and Axis-Invariants, which have the benefits of iterative structure and can avoid complex derivation of traditional dynamics modeling methods. Then, an attitude stabilization strategy consisting of improved nonlinear model predictive control and a hybrid actuator is implemented to handle the disturbance generated by the manipulation of multiple robot arms. The hybrid actuator can provide accurate control torque while simultaneously avoiding the singularity and saturation of the control moment gyro and reaction wheel, respectively. Finally, a scenario of space debris recycling is used to demonstrate the effectiveness of the proposed modeling and control strategy for on-orbit servicing missions with multiarmed space robots. (C) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

关键词： creativity   educational robotics   pedagogical practices   instructional framework  

摘要： This study explored how educational robotics (ER) was implemented in classrooms to foster creativity among elementary school students and identified challenges associated with its implementation. Twenty-six teachers at different elementary schools were interviewed. In-depth teacher interviews and grounded theory were used to collect and analyze the interviews. We found that the intended creative learning outcome for students was mastery of the developmental process of creativity. The teachers generally reported using a four-phase instructional framework consisting of eight sub-phases and targeted teaching strategies to support students' learning outcomes. Challenges included insufficient appropriate learning materials, a lack of expansive learning activities and tasks and limited opportunities to engage students in the process of design thinking and developing metacognitive abilities. The findings have practical implications for teachers and researchers who are interested in developing pedagogical practices (PP) incorporating ER to support students' creativity. The study also has theoretical value, offering insights into teachers' PP in implementing ER.

关键词： Educational platforms   Teaching strategy   Computer simulations   Educational innovation  

摘要： Previous studies show that traditional teaching methods such as oral explanations and PowerPoint presentations can be complemented with the use of computer simulations in problem-solving sessions to teach robotics. Nevertheless, these previous works rest upon the assumption that the knowledge that is learned in virtual laboratories transfers to its equivalent real task. The main contribution of this work is to validate that the knowledge obtained by students in an undergraduate robotics course using computer simulations of 3D model robots can be applied to its real-world context. The experimental platform used to run the computer simulations was based on the Simscape Multibody library of the MATLAB (TM) software. Results show a satisfactory knowledge transfer because more than 75% of the students finished a forward kinematics problem using a physical manipulator built with LEGO Mindstorms (TM). In addition, the observation analysis of the professor reveals that students reinforced their knowledge previously learned, and their problem-solving and critical thinking skills also improved. In this way, this study demonstrates that the proposed methodology not only helps the transfer of knowledge to the real-world context but also helps to develop student competencies. Future work is needed to replicate the findings in other robotics topics, such as the generation of trajectories, the analysis of the dynamics of manipulators, and the design of various controllers for the actuators of the robot.

关键词： bronchoscopy   lung biopsy   lung cancer   robotic bronchoscopy   solitary pulmonary nodule  

摘要： Bronchoscopic sampling of PPL was significantly advanced by the development of the endobronchial ultrasound guide sheath method in the 1990s. Since then, a range of technical and procedural techniques have further advanced diagnostic yields. These include the use of thinner bronchoscopes with better working channel diameters, understanding the importance of peripheral transbronchial needle aspiration, and virtual bronchoscopic assistance. These have enabled better sampling of smaller and more technically challenging lesions including ground-glass nodules. Most recently, robotic bronchoscopy has been developed which, among other refinements, allows fine control of visual bronchoscopic navigation by replacing movements directed by the hand with electronic consoles and trackballs, and innovatively integrate virtual with real bronchoscopic pathways. The requirement for PPL diagnosis and treatment is expected to increase with more chest CT performed as part of CT screening programmes.