3,248 research outputs found
Using Python to Program LEGO MINDSTORMS Robots: The PyNXC Project
LEGO MINDSTORMSÂź NXT (Lego Group, 2006) is a perfect platform for introducing programming concepts, and is generally targeted toward children from age 8-14. The language which ships with the MINDSTORMSÂź, called NXTg, is a graphical language based on LabVIEW (Jeff Kodosky, 2010). Although there is much value in graphical languages, such as LabVIEW, a text-based alternative can be targeted at an older audiences and serve as part of a more general introduction to modern computing. Other languages, such as NXC (Not Exactly C) (Hansen, 2010) and PbLua (Hempel, 2010), fit this description. Here we introduce PyNXC, a subset of the Python language which can be used to program the NXT MINDSTORMSÂź. We present results using PyNXC, comparisons with other languages, and some challenges and future possible extensions
'Playing robot': an interactive sound installation in human-robot interaction design for new media art
In this study artistic human-robot interaction design is in- troduced as a means for scientific research and artistic inves- tigations. It serves as a methodology for situated cognition integrating empirical methodology and computational mod- eling, and is exemplified by the installation playing robot. Its artistic purpose is to aid to create and explore robots as a new medium for art and entertainment. We discuss the use of finite state machines to organize robotsâ behavioral reac- tions to sensor data, and give a brief outlook on structured observation as a potential method for data collection
Mobile Robot Lab Project to Introduce Engineering Students to Fault Diagnosis in Mechatronic Systems
This document is a self-archiving copy of the accepted version of the paper.
Please find the final published version in IEEEXplore: http://dx.doi.org/10.1109/TE.2014.2358551This paper proposes lab work for learning fault detection and diagnosis (FDD) in mechatronic systems. These skills are important for engineering education because FDD is a key capability of competitive processes and products. The intended outcome of the lab work is that students become aware of the importance of faulty conditions and learn to design FDD strategies for a real system. To this end, the paper proposes a lab project where students are requested to develop a discrete event dynamic system (DEDS) diagnosis to cope with two faulty conditions in an autonomous mobile robot task. A sample solution is discussed for LEGO Mindstorms NXT robots with LabVIEW. This innovative practice is relevant to higher education engineering courses related to mechatronics, robotics, or DEDS. Results are also given of the application of this strategy as part of a postgraduate course on fault-tolerant mechatronic systems.This work was supported in part by the Spanish CICYT under Project DPI2011-22443
How does peoplesâ perception of control depend on the criticality of a task performed by a robot Paladyn
© 2019 Adeline Chanseau et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 Public License.Robot companions are starting to become more common and people are becoming more familiar with devices such as Google Home, Alexa or Pepper,one must wonder what is the optimum way for people to control their devices? This paper provides presents an investigation into how much direct control people want to have of their robot companion and how dependent this is on the criticality of the tasks the robot performs. A live experiment was conducted in the University of Hertfordshire Robot House, with a robot companion performing four different type of tasks. The four tasks were: booking a doctorâs appointment, helping the user to build a Lego character, doing a dance with the user, and carrying biscuits for the user. The selection of these tasks was based on our previous research to define tasks which were relatively high and low in criticality. The main goal of the study was to find what level of direct control over their robot participants and if this was dependent on the criticality of the task performed by the robot. Fifty people took part in the study, and each experienced every task in a random order. Overall,it was found that participantsâ perception of control was higher when the robot was performing a task in a semi-autonomous mode. However, for the task "carrying biscuits", although participants perceived to be more in control with the robot performing the task in a semi autonomous mode, they actually preferred to have the robot performing the task automatically (where they felt less in control). The results also show that, for the task "booking a doctorâs appointment", considered to be the most critical of all four tasks, participants did not prefer that the robot chose the date of the appointment as they felt infantilised.Peer reviewe
Integrating mobile robotics and vision with undergraduate computer science
This paper describes the integration of robotics education into an undergraduate Computer Science curriculum. The proposed approach delivers mobile robotics as well as covering the closely related field of Computer Vision, and is directly linked to the research conducted at the authorsâ institution. The paper describes the most relevant details of the module content and assessment strategy, paying particular attention to the practical sessions using Rovio mobile robots. The specific choices are discussed that were made with regard to the mobile platform, software libraries and lab environment. The paper also presents a detailed qualitative and quantitative analysis of student results, including the correlation between student engagement and performance, and discusses the outcomes of this experience
A Playful Experiential Learning System With Educational Robotics
This article reports on two studies that aimed to evaluate the effective impact of
educational robotics in learning concepts related to Physics and Geography. The
reported studies involved two courses from an upper secondary school and two courses
froma lower secondary school. Upper secondary school classes studied topics ofmotion
physics, and lower secondary school classes explored issues related to geography.
In each grade, there was an âexperimental groupâ that carried out their study using
robotics and cooperative learning and a âcontrol groupâ that studied the same concepts
without robots. Students in both classes were subjected to tests before and after the
robotics laboratory, to check their knowledge in the topics covered. Our initial hypothesis
was that classes involving educational robotics and cooperative learning are more
effective in improving learning and stimulating the interest and motivation of students.
As expected, the results showed that students in the experimental groups had a far
better understanding of concepts and higher participation to the activities than students
in the control groups
Kick control: using the attracting states arising within the sensorimotor loop of self-organized robots as motor primitives
Self-organized robots may develop attracting states within the sensorimotor
loop, that is within the phase space of neural activity, body, and
environmental variables. Fixpoints, limit cycles, and chaotic attractors
correspond in this setting to a non-moving robot, to directed, and to irregular
locomotion respectively. Short higher-order control commands may hence be used
to kick the system from one self-organized attractor robustly into the basin of
attraction of a different attractor, a concept termed here as kick control. The
individual sensorimotor states serve in this context as highly compliant motor
primitives.
We study different implementations of kick control for the case of simulated
and real-world wheeled robots, for which the dynamics of the distinct wheels is
generated independently by local feedback loops. The feedback loops are
mediated by rate-encoding neurons disposing exclusively of propriosensoric
inputs in terms of projections of the actual rotational angle of the wheel. The
changes of the neural activity are then transmitted into a rotational motion by
a simulated transmission rod akin to the transmission rods used for steam
locomotives.
We find that the self-organized attractor landscape may be morphed both by
higher-level control signals, in the spirit of kick control, and by interacting
with the environment. Bumping against a wall destroys the limit cycle
corresponding to forward motion, with the consequence that the dynamical
variables are then attracted in phase space by the limit cycle corresponding to
backward moving. The robot, which does not dispose of any distance or contact
sensors, hence reverses direction autonomously.Comment: 17 pages, 9 figure
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