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Machines: Problem Solving I

Machines: Problem Solving I

A toggle clamp is a mechanical device commonly used for holding and clamping objects in various applications, such as woodworking, metalworking, and assembly operations. Consider a toggle clamp subjected to a force of 200 N at the handle. The vertical clamping force can be calculated, provided the dimensions of the toggle clamp are known.
The toggle clamp system is a machine structure consisting of movable, pin-connected multi-force members that form a stabilized system to transmit forces. The...

Machines: Problem Solving II

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Machines are complex structures consisting of movable, pin-connected multi-force members that work together to transmit forces. Consider a lifting tong carrying a 100 kg load. It comprises movable sections DAF and CBG linked together with member AB.

Screw: Problem Solving

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In mechanical engineering, the interaction between a threaded screw shaft and a plate gear involves analyzing the resisting torque on the plate gear that can be overpowered when a specific torsional moment is applied to the shaft. To better comprehend this concept, consider a generic situation with a threaded screw shaft with a given mean radius and lead and a plate gear with a specified mean radius. The coefficient of static friction between the screw and gear is also provided.
To evaluate the...

Cognitive Learning

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E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
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E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a bonus...

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Effective problem-solving consists of two steps: 1. identifying the problem and 2. selecting the appropriate problem-solving strategy (i.e., a plan of action used to find a solution). Humans use four problem-solving strategies:

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Related Experiment Video

Updated: Jun 22, 2026

Designing and Implementing Nervous System Simulations on LEGO Robots

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Published on: May 25, 2013

MiniCERNBot Educational Platform: Antimatter Factory Mock-up Missions for Problem-Solving STEM Learning.

Josep Marín Garcés¹, Carlos Veiga Almagro^1,2, Giacomo Lunghi²

¹CERN, BE-CEM Controls, Electronics and Mechatronics Group, 1217 Geneva, Switzerland.

Sensors (Basel, Switzerland)

|March 6, 2021

Summary

The MiniCERNBot platform enhances STEM education by providing hands-on robotics experience. This educational tool allows students to develop multidisciplinary skills through collaborative, problem-solving activities inspired by real scientific operations.

Keywords:

STEM education education engineering education interaction mechatronics physical devices robotics sensors

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Area of Science:

Mechatronics and Robotics
STEM Education

Background:

Robotics and mechatronics are effective tools for STEM education.
Students can create innovative solutions with real-world impact.

Purpose of the Study:

Present the MiniCERNBot Educational Robotic platform for high-school and university students.
Improve STEM educational activities and collaborations between CERN and other institutions.

Main Methods:

Developed a comprehensive educational system with tutorials and tasks for various ages.
Designed a robot inspired by CERN's robotic systems and operations.
Described the software and hardware architecture, and analyzed modularity and network performance.

Main Results:

The MiniCERNBot platform offers learning paths for different ages and disciplines.
The system demonstrates modularity and effective network performance during educational exercises.
The platform facilitates collaborative problem-solving and enhances student motivation.

Conclusions:

The MiniCERNBot platform effectively improves STEM education and dissemination at CERN.
It fosters inter-institutional collaboration and inspires students towards technical studies.
The platform enables students to practice multidisciplinary STEM skills through real-world inspired activities.