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Contribution: This article provides evidence that perceived learning has a relationship and influences the way students evaluate laboratory experiments, facilities, and demonstrators. Background: Debate continues on the capability and/or reliability of students to evaluate teaching and/or learning. Understanding such relationships can help educators decode evaluation data to develop more effective teaching experiences. Research Question: Does a relationship exist between student evaluation scores and perceived learning? Methodology: Perceived learning across the cognitive, psychomotor, and affective domains was measured using the Laboratory Learning Objectives Measurement (LLOM) tool at an Australian (344 students) and Serbian (181 students) university. A multilevel statistical analysis was conducted. Findings: Statistically significant relationships were found between student evaluation scores and perceived learning across the cognitive, psychomotor, and affective domains with some differences found between the two universities. This provides evidence that perceived learning plays a role in influencing student evaluation scores. Students perceived an improvement of learning across all three domains confirming the multifaceted benefits of the laboratory for engineering education.

The laboratory is an integral component of engineering education, resulting in a multitude of studies. Generally, the research focus is on the laboratory innovation, rather than learning itself. It is observed that empirical evidence is strongly built around student perceptions of their learning or experience via survey instruments; and in some cases, complimented with limited quantitative measures including assessments. With the laboratory being a multifaceted, multi-domain learning environment also covering the psychomotor and affective domains, such observations suggest that the empirical data being collected is providing an incomplete analysis. Therefore, this paper undertakes a systematic literature review exploring remote, simulation and traditional laboratory studies that explicitly include assessment analysis. Explored are the types of assessments used and assessment innovations. The study 1) confirms that assessments concentrate on the cognitive domain, underselling the learning being achieved; 2) Student survey instruments play an important role in measuring laboratory success; 3) Background information of the learning objectives are not clearly stated and/or not clearly linked to the associated assessment; 4) There are several research opportunities available to improve understanding of laboratory assessments. A roadmap and recommendations to overcome these weaknesses is outlined, providing a platform for future researchers to incorporate in their studies.

Purpose: The purpose of this paper is to present an improved concept of software-based laboratory exercises, namely a Virtual Laboratory for Engineering Sciences (VLES). Design/methodology/approach: The implementation of distance learning and e-learning in engineering sciences (such as Mechanical and Electrical Engineering) is still far behind current practice in narrative disciplines (Economics, Management, etc.). This is because education in technical disciplines requires laboratory exercises, providing skill-acquisition and hands-on experience. In order to overcome this problem for distance-learning developers and practitioners, a new modular and hierarchically organized approach is needed. Findings: The concept involves simulation models to emulate system dynamics, full virtual reality to provide visualization, advanced social-clubbing to ensure proper communication, and an AI tutor to supervise the lab work. Its modularity and hierarchical organization offer the possibility of applying the concept to practically any engineering field: a higher level provides the general framework--it considers lab workplaces as objects regardless of the technical field they come from, and provides communication and supervision--while the lower level deals with particular workplaces. An improved student's motivation is expected. Originality/value: The proposed concept aims rather high, thus making the work truly challenging. With the current level of information and communication technologies, some of the required features can only be achieved with difficulty; however, the rapid growth of the relevant technologies supports the eventual practicality of the concept. This paper is not intended to present any final results, solutions, or experience. The idea is to promote the concept, identify problems, propose guidelines, and possibly open a discussion. (Contains 15 figures, 1 table, and 4 notes.)

Non-ergonomic execution of repetitive physical tasks represents a major cause of work-related musculoskeletal disorders (WMSD). This study was focused on the pushing and pulling (P&P) of an industrial handcart (which is a generic physical task present across many industries), with the aim to investigate the dependence of P&P execution on the operators' psychological status and the presence of pain syndromes of the upper limbs and spine. The developed acquisition system integrated two three-axis force sensors (placed on the left and right arm) and six electromyography (EMG) electrodes (placed on the chest, back, and hand flexor muscles). The conducted experiment involved two groups of participants (with and without increased psychological scores and pain syndromes). Ten force parameters (for both left and right side), one EMG parameter (for three different muscles, both left and right side), and two time-domain parameters were extracted from the acquired signals. Data analysis showed intergroup differences in the examined parameters, especially in force integral values and EMG mean absolute values. To the best of our knowledge, this is the first study that evaluated the composite effects of pain syndromes, spine mobility, and psychological status of the participants on the execution of P&P tasks—concluding that they have a significant impact on the P&P task execution and potentially on the risk of WMSD. The future work will be directed towards the development of a personalized risk assessment system by considering more muscle groups, supplementary data derived from operators' poses (extracted with computer vision algorithms), and cognitive parameters (extracted with EEG sensors). [ABSTRACT FROM AUTHOR]

An autonomous robot is often in a situation to perform tasks or missions in an initially unknown environment. A logical approach to doing this implies discovering the environment by the incremental principle defined by the applied exploration strategy. A large number of exploration strategies apply the technique of selecting the next robot position between candidate locations on the frontier between the unknown and the known parts of the environment using the function that combines different criteria. The exploration strategies based on Multi-Criteria Decision-Making (MCDM) using the standard SAW, COPRAS and TOPSIS methods are presented in the paper. Their performances are evaluated in terms of the analysis and comparison of the influence that each one of them has on the efficiency of exploration in environments with a different risk level of a “bad choice” in the selection of the next robot position. The simulation results show that, due to its characteristics related to the intention to minimize risk, the application of TOPSIS can provide a good exploration strategy in environments with a high level of considered risk. No significant difference is found in the application of the analyzed MCDM methods in the exploration of environments with a low level of considered risk. Also, the results confirm that MCDM-based exploration strategies achieve better results than strategies when only one criterion is used, regardless of the characteristics of the environment. The famous D* Lite algorithm is used for path planning. [ABSTRACT FROM AUTHOR]

The use of robotics in health care has seen a recent rise in interest due to its potential for use during the SARS-CoV-2 pandemic. The transmission rate of COVID-19 has meant that health-care workers are under increasing pressure, risks, and workload to manage the requirements of personal protective equipment, strict disinfection procedures, and the heightened medical needs of patients. Patients are suffering from isolation, and not just in hospitals: higher-risk individuals must shelter, meaning social interactions, particularly in care homes, are limited. Robots can help by providing disinfection and logistics services that support patients and health-care professionals, by acting as devices to be used for rehabilitation at home (for both pre-existing conditions and for COVID-19-related treatment), and via interventional systems that can widely distribute future vaccinations. [ABSTRACT FROM AUTHOR]

Considerations of energy efficiency and safe human-robot interaction have led to an increase in the exploitation of compliance in robotics, and much of this work has been inspired by biological systems. As a consequence, new analytical tools are now required in order to enable the dynamic analysis of these novel compliant robots, especially in their interactions with the environment. This paper extends the ‘Flier’ approach to show how it could be applied to the dynamic analysis of contact tasks involving a highly compliant biologically inspired robot – in this case an anthropomimetic robot, a humanoid with a human-like skeleton and artificial muscles, in which the joints are actuated by DC motors acting via compliant tendon transmissions. First, a computer-based model of the robot’s dynamics is developed. Various constraints are then introduced to describe the contacts (including impacts) with the ground, and with objects in the environment. Simulation results are presented for two types of interactions with the external world: a grasping task and the case of the robot moving on a mobile base. [ABSTRACT FROM PUBLISHER]

Anthropomimetic robotics differs from conventional approaches by capitalizing on the replication of the inner structures of the human body, such as muscles, tendons, bones, and joints. Here we present our results of more than three years of research in constructing, simulating, and, most importantly, controlling anthropomimetic robots. We manufactured four physical torsos, each more complex than its predecessor, and developed the tools required to simulate their behavior. Furthermore, six different control approaches, inspired by classical control theory, machine learning, and neuroscience, were developed and evaluated via these simulations or in small-scale setups. While the obtained results are encouraging, we are aware that we have barely exploited the potential of the anthropomimetic design so far. But, with the tools developed, we are confident that this novel approach will contribute to our understanding of morphological computation and human motor control in the future. [ABSTRACT FROM AUTHOR]

This paper proposes a new control strategy for noncompliant and compliant antagonistic tendon drives. It is applied to a succession of increasingly complex single-joint systems, starting with a linear and noncompliant system and ending with a revolute, nonlinearly tendon coupled and compliant system. The last configuration mimics the typical human joint structure, used as a model for certain joints of the anthropomimetic robot ECCEROBOT. The control strategy is based on a biologically inspired pullerfollower concept, which distinguishes the roles of the agonist and antagonist motors. One actuator, the puller, is considered as being primarily responsible for the motion, while the follower prevents its tendon from becoming slack by maintaining its tendon force at some non-zero level. Certain movements require switching actuator roles; adaptive co-contraction is used to prevent tendons slackening, while maintaining energetic efficiency. The single-joint control strategy is then evaluated in a multijoint system. Dealing with the gravitational and dynamic effects arising from the coupling in a multi-joint system, a robust control design has to be applied with on-line gravity compensation. Finally, an experiment corresponding to object grasping is presented to show the controller's robustness to external disturbances. [ABSTRACT FROM AUTHOR]

The progress in the research of various areas of robotics, artificial intelligence, and other similar scientific disciplines enabled the application of multi-robot systems in different complex environments and situations. It is necessary to elaborate the strategies regarding the path planning and paths coordination well in order to efficiently execute a global mission in common environment, prior to everything. This paper considers the multi-robot system based on the cloud technology with a high level of autonomy, which is intended for execution of tasks in a complex and crowded environment. Cloud approach shifts computation load from agents to the cloud and provides powerful processing capabilities to the multi-robot system. The proposed concept uses a multi-robot path planning algorithm that can operate in an environment that is unknown in advance. With the aim of improving the efficiency of path planning, the implementation of Multi-criteria decision making (MCDM) while using Full consistency method (FUCOM) is proposed. FUCOM guarantees the consistent determination of the weights of factors affecting the robots motion to be symmetric or asymmetric, with respect to the mission specificity that requires the management of multiple risks arising from different sources, optimizing the global cost map in that way. [ABSTRACT FROM AUTHOR]