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Educational robots offer a platform for training aspiring engineers and building trust in technology that is envisioned to shape how we work and live. In education, accessibility and modularity are significant in the choice of such a technological platform. In order to foster continuous development of the robots as well as to improve student engagement in the design and fabrication process, safe production methods with low accessibility barriers should be chosen. In this paper, we present Robotont 3, an open-source mobile robot that leverages Fused Deposition Modeling (FDM) 3D-printing for manufacturing the chassis and a single dedicated system board that can be ordered from online printed circuit board (PCB) assembly services. To promote accessibility, the project follows open hardware practices, such as design transparency, permissive licensing, accessibility in manufacturing methods, and comprehensive documentation. Semantic Versioning was incorporated to improve maintainability in development. Compared to the earlier versions, Robotont 3 maintains all the technical capabilities, while featuring an improved hardware setup to enhance the ease of fabrication and assembly, and modularity. The improvements increase the accessibility, scalability and flexibility of the platform in an educational setting.

Remote, online learning provides opportunities for flexible, accessible, and personalised education, regardless of geographical boundaries. This study mode also promises to democratise education, making it more adaptable to individual learning styles. However, transitioning to this digital paradigm also brings challenges, including issues related to students’ mental health and motivation and communication barriers. Integrating social robots into this evolving educational landscape presents an effective approach to enhancing student support and engagement. In this article, we focus on the potential of social robots in higher education, identifying a significant gap in the educational technology landscape that could be filled by open-source learning robots tailored to university students’ needs. To bridge this gap, we introduce the Robotic Study Companion (RSC), a customisable, open-source social robot developed with cost-effective off-the-shelf parts. Designed to provide an interactive and multimodal learning experience, the RSC aims to enhance student engagement and success in their studies. This paper documents the development of the RSC, from establishing literature-based requirements to detailing the design process and build instructions. As an open development platform, the RSC offers a solution to current educational challenges and lays the groundwork for personalised, interactive, and affordable AI-enabled robotic companions.

In order to achieve visionary concepts such as Society 5.0 and Industry 5.0, there is a growing need for people who are able to create innovative robotic technologies. Training students to become such skilled professionals requires transitioning from often toy-like educational platforms with significant hardware limitations to costly research robots with full ROS (Robot Operating System) support. To aid in this transition, we propose Robotont – an open-source omnidirectional mobile robot platform with both physical hardware and a digital twin. Robotont enables robotics education with professional tools as well as provides researchers with a capable mobility platform for validating and demonstrating scientific results. Robotont has successfully been used for university teaching, professional education, and online courses about ROS and robotics.

In hospitals, trained medical staff are often, in addition to performing complex procedures, spending valuable time on secondary tasks such as transporting samples and medical equipment; or even guiding patients and visitors around the premises. If these non-medical tasks were automated by deploying mobile service robots, more time can be focused on treating patients or allowing well-deserved rest for the potentially overworked healthcare professionals. Automating such tasks requires a human-aware robotic mobility system that can among other things navigate the hallways of the hospital; predictively avoid collisions with humans and other dynamic obstacles; coordinate task distribution and area coverage within a fleet of robots and other IoT devices; and interact with the staff, patients and visitors in an intuitive way. This work presents the results, lessons-learned and the source code of deploying a heterogeneous mobile robot fleet at the Tartu University Hospital, performing object transportation tasks in areas of intense crowd movement and narrow hallways. The primary use-case is defined as transporting time-critical samples from an intensive care unit to the hospital lab. Our work builds upon Robotics Middleware Framework (RMF), an open source, actively growing and highly capable fleet management platform which is yet to reach full maturity. Thus this paper demonstrates and validates the real-world deployment of RMF in an hospital setting and describes the integration efforts.

Joint space trajectory optimization under end-effector task constraints leads to a challenging non-convex problem. Thus, a real-time adaptation of prior computed trajectories to perturbation in task constraints often becomes intractable. Existing works use the so-called warm-starting of trajectory optimization to improve computational performance. We present a fundamentally different approach that relies on deriving analytical gradients of the optimal solution with respect to the task constraint parameters. This gradient map characterizes the direction in which the prior computed joint trajectories need to be deformed to comply with the new task constraints. Subsequently, we develop an iterative line-search algorithm for computing the scale of deformation. Our algorithm provides near real-time adaptation of joint trajectories for a diverse class of task perturbations, such as (i) changes in initial and final joint configurations of end-effector orientation-constrained trajectories and (ii) changes in end-effector goal or way-points under end-effector orientation constraints. We relate each of these examples to real-world applications ranging from learning from demonstration to obstacle avoidance. We also show that our algorithm produces trajectories with quality similar to what one would obtain by solving the trajectory optimization from scratch with warm-start initialization. Most importantly, however, our algorithm achieves a worst-case speed-up of 160x over the latter approach.

Teaching robotics with the robot operating system (ROS) is valuable for instating good programming practices but requires significant setup steps from the learner. Providing a ready-made ROS learning environment over the web can make robotics more accessible; however, most of the previous remote labs have abstracted the authentic ROS developer environment either for didactical or technological reasons, or do not give the possibility to program physical robots. In this article, we present a remote web lab that employs virtual network computing and Docker to serve in-browser desktop workstations, where learning tasks can be completed on both the physical and simulated robots. The learners can reserve access to the remote lab through a learning management interface, which also includes tools for administering the remote lab. The system allows anyone to experiment with ROS without configuring any software locally and was successfully trialed in an online ROS course.

Ionic electromechanically active polymers (IEAP) are laminar composites that can be considered attractive candidates for soft actuators. Their outstanding properties such as low operating voltage, easy miniaturization, and noiseless operation are, however, marred by issues related to the repeatability in the production and operation of these materials. Implementing closed-loop control for IEAP actuators is a viable option for overcoming these issues. Since IEAP laminates also behave as mechanoelectrical sensors, it is advantageous to combine the actuating and sensing functionalities of a single device to create a so-called self-sensing actuator. This review article systematizes the state of the art in producing self-sensing ionic polymer actuators. The IEAPs discussed in this paper are conducting (or conjugated) polymers actuators (CPA), ionic polymer-metal composite (IPMC), and carbonaceous polymer laminates.

Mitmed üliõpilaste seas läbi viidud uuringud näitavad seost epistemoloogiliste uskumuste ehk teadmuskäsituse ja õpikäsituse vahel. Need uskumused ise aga tingivad selle, kuidas üliõpilased võtavad vastu erinevaid õppejõu tegevusi ja kuidas nad õpivad. Viimasel ajal levivad ka Eestis üha enam aktiivõppe meetodid, mis eeldavad üliõpilastelt teistsugust valmisolekut kui passiivne loengu vormis õppimine. Käesoleva töö eesmärk oligi kirjeldada, millised on Eesti esimese kursuse üliõpilaste epistemoloogilised uskumused ja õpikäsitus ning kuidas need mõjutavad üliõpilaste õpieelistusi. Lähtuti hüpoteesist, et Eesti esmakursuslased on pigem passiivsed, fikseeritud laadi epistemoloogiliste uskumustega ning ootavad õppejõult kui autoriteedilt nn valmisteadmisi. Seetõttu eelistavad nad töötada pigem üksi, mitte rühmas.Uurimuse hüpotees leidis üldjoontes kinnitust. Enamik uuritud esimese kursuse üliõpilastest käsitab teadmist oskuse või kogemusena. Õppimine on uute teadmiste omandamine õppejõult, kaaslastel on eelkõige vaid motiveeriv roll. Esmakursuslased eelistavad õppejõudu, kes on autoriteet ja ekspert, mistõttu oodatakse, et õppejõud tooks elulisi näiteid ja selgitaks õpitavat samm-sammult. Suur osa küsimustiku täitnud üliõpilastest on pindmise õpihoiakuga: nad mõistavad teadmist eelkõige fakti, kogemuse või oskusena ja eelistavad õppida üksi. Samal ajal on neil pluralistlikku laadi epistemoloogilised uskumused. Uuringust selgus ka, et sügava õpihoiakuga üliõpilased näevad õppimist protsessina ning teadmisi sealjuures ajas muutuvate ja arenevatena.Ainsaks kõrvalekaldeks esialgsest hüpoteesist olid üliõpilaste valdavalt pluralistlikud epistemoloogilised uskumused, mis võivad viidata ühiskonnas üldiselt levivale arusaamale, et pole ühtset tõde, vaid on palju tõlgendusi. Summary

We present a study of an electrical model of electromechanically active carbon-polymer composite (CPC) with carbide-derived carbon (CDC) electrodes. The major focus is on investigation of surface electrode behavior upon external bending of the material. We show that electrical impedance measured from the surface of the CDC-based CPC can be used to determine the curvature of the material and, hence, the tip displacement of a CPC laminate in a cantilever configuration. It is also shown that by measuring surface signals in the process of an actuator’s work-cycle, we obtain a self-sensing collision-detecting CPC actuator that can be considered as a counterpart of biomimetic vibrissae.

Teleoperated mobile robots, equipped with object manipulation capabilities, provide safe means for executing dangerous tasks in hazardous environments without putting humans at risk. However, mainly due to a communication delay, complex operator interfaces and insufficient Situational Awareness (SA), the task productivity of telerobots remains inferior to human workers. This paper addresses the shortcomings of telerobots by proposing a combined approach of (i) a scalable and intuitive operator interface with gestural and verbal input, (ii) improved Situational Awareness (SA) through sensor fusion according to documented best practices, (iii) integrated virtual fixtures for task simplification and minimizing the operator’s cognitive burden and (iv) integrated semiautonomous behaviors that further reduce cognitive burden and negate the impact of communication delays, execution latency and/or failures. The proposed teleoperation system, TeMoto, is implemented using ROS (Robot Operating System) to ensure hardware agnosticism, extensibility and community access. The operator’s command interface consists of a Leap Motion Controller for hand tracking, Griffin PowerMate USB as turn knob for scaling and a microphone for speech input. TeMoto is evaluated on multiple robots including two mobile manipulator platforms. In addition to standard, task-specific evaluation techniques (completion time, user studies, number of steps, etc.)—which are platform and task dependent and thus difficult to scale—this paper presents additional metrics for evaluating the user interface including task-independent criteria for measuring generalized (i) task completion efficiency and (ii) operator context switching.

Ionic electromechanically active polymers (IEAPs) are considered attractive candidates for soft, miniature, and lightweight actuators. The bucky-gel actuator is a carbonaceous subtype of IEAP that due to its structure (i.e. two highly porous electrodes sandwiching a thin ion-permeable electrolyte layer) and composition (i.e. being composed of soft porous polymer, carbon nanotubes, and ionic liquid) is very similar to an electric double-layer capacitor. In response to the voltage applied between the electrodes of a bucky-gel actuator, the laminar structure bends. The time domain behavior exhibits, however, a phenomenon called the back-relaxation, i.e., after some time the direction of bending is reversed even though voltage remains constant. In spite of the working mechanism of IEAP actuators being generally attributed to the transport of ions within the soft multilayer system, the specific details remain unclear. A so-called two-carrier model proposes that the bending and subsequent back-relaxation are caused by the relocation of two ionic species having different mobilities as they enter and exit the electrode layers. By adopting the two-carrier model for bucky-gel actuators, we see very good agreement between the mathematical representation and the experimental data of the electromechanical behavior. Furthermore, since the bucky-gel actuator is viscoelastic, we propose to use the time domain response of a blocking force as the key parameter related to the inner ionic mechanism. We also introduce a method to estimate the viscoelastic creep compliance function from the time domain responses for curvature and blocking force. This analysis includes four types of bucky-gel actuators of varying composition and structure. [ABSTRACT FROM AUTHOR]