Student groups are challenged to program robots with light sensors to follow a black line. Learning both the logic and skills behind programming robots for this challenge helps students improve their understanding of how robots "think" and widens their appreciation for the complexity involved in programming LEGO® MINDSTORMS® NXT robots to do what appears to be a simple task. They test their ideas for approaches to solve the problem and ultimately learn a (provided) working programming solution. They think of real-world applications for line-follower robots that use sensor input. A PowerPoint® presentation and pre/post quizzes are provided.

Students are challenged to design and program Arduino-controlled robots that behave like simple versions of the automated guided vehicles engineers design for real-world applications. Using Arduino microcontroller boards, infrared (IR) sensors, servomotors, attachable wheels and plastic containers (for the robot frame), they make "Lunch-Bots." Teams program the robots to meet the project constraints—to follow a line of reflective tape, make turns and stop at a designated spot to deliver a package, such as a sandwich or pizza slice. They read and interpret analog voltages from IR sensors, compare how infrared reflects differently off different materials, and write Arduino programs that use IR sensor inputs to control the servomotors. Through the process, students experience the entire engineering design process. Pre/post-quizzes and coding help documents are provided.

Based on their experience exploring the Mars rover Curiosity and learning about what engineers must go through to develop a vehicle like Curiosity, students create Android apps that can control LEGO MINDSTORMS(TM) NXT robots, simulating the difficulties the Curiosity rover could encounter. The activity goal is to teach students programming design and programming skills using MIT's App Inventor software as the vehicle for the learning. The (free to download) App Inventor program enables Android apps to be created using building blocks without having to actually know a programming language. At activity end, students are ready to apply what they learn to write other applications for Android devices.

As part of a design challenge, students learn how to use a rotation sensor (located inside the casing of a LEGO® MINDSTORMS ® NXT motor) to measure how far a robot moves with each rotation. Through experimentation and measurement with the sensor, student pairs determine the relationship between the number of rotations of the robot's wheels and the distance traveled by the robot. Then they use this ratio to program LEGO robots to move precise distances in a contest of accuracy. The robot that gets closest to the goal without touching the toy figures at the finish line is the winning programming design. Students learn how rotational sensors measure distance, how mathematics can be used for real-world purposes, and about potential sources of error due to gearing when using rotation sensor readings for distance calculations. They also become familiar with the engineering design process as they engage in its steps, from understanding the problem to multiple test/improve iterations to successful design.

Students investigate the materials properties such as acoustical absorptivity, light reflectivity, thermal conductivity, hardness, and water resistance of various materials. They use sound, light and temperature sensors to collect data on various materials. They practice making design decisions about what materials would be best to use for specific purposes and projects, such as designing houses in certain environments to meet client requirements. After testing, they use the provided/tested materials to design and build model houses to meet client specifications.

Students experience data collection, analysis and inquiry in this LEGO® MINDSTORMS® NXT -based activity. They measure the position of an oscillating platform using a ultrasonic sensor and perform statistical analysis to determine the mean, mode, median, percent difference and percent error for the collected data.

Students learn about sound waves and use them to measure distances between objects. They explore how engineers incorporate ultrasound waves into medical sonogram devices and ocean sonar equipment. Students learn about properties, sources and applications of three types of sound waves, known as the infra-, audible- and ultra-sound frequency ranges. They use ultrasound waves to measure distances and understand how ultrasonic sensors are engineered.

Students learn first-hand the relationship between force, area and pressure. They use a force sensor built from a LEGO® MINDSTORMS® NXT kit to measure the force required to break through a paper napkin. An interchangeable top at the end of the force sensor enables testing of different-sized areas upon which to apply pressure. Measuring the force, and knowing the area, students compute the pressure. This leads to a concluding discussion on how these concepts are found and used in engineering and nature.

Using the LEGO MINDSTORMS(TM) NXT kit, students construct experiments to measure the time it takes a free falling body to travel a specified distance. Students use the touch sensor, rotational sensor, and the NXT brick to measure the time of flight for the falling object at different release heights. After the object is released from its holder and travels a specified distance, a touch sensor is triggered and time of object's descent from release to impact at touch sensor is recorded and displayed on the screen of the NXT. Students calculate the average velocity of the falling object from each point of release, and construct a graph of average velocity versus time. They also create a best fit line for the graph using spreadsheet software. Students use the slope of the best fit line to determine their experimental g value and compare this to the standard value of g.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Tireless as robots may seem, even they need a break sometimes. Taking a cue from nature, researchers have designed a mechanical claw that allows drones to perch in between jobs. Birds of prey save energy by perching on branches, eaves, cables, and other elevated structures. This three-toed mechanical claw helps drones do the same. Able to deform actively or passively, this claw allows drones to perch in between jobs and supports more than 15 times its own weight, without straining the power supply of the flying machines that carry it. Perching is controlled manually by remote, but efforts to automate this action are currently underway, providing a way to give even the hardest-working robots a break..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Students work as engineers to learn about the properties of molecules and how they move in 3D space through the use of LEGO MINDSTORMS(TM) NXT robotics. They design and build molecular models and use different robotic sensors to control the movement of the molecular simulations. Students learn about the size of atoms, Newman projections, and the relationship of energy and strain on atoms. This unique modular modeling activity is especially helpful in providing students with a spatial and tactile understanding of how molecules behave.

This activity helps students understand the significance of programming and also how the LEGO MINDSTORMS(TM) NXT robot's sensors assist its movement and make programming easier. Students compare human senses to robot sensors, describing similarities and differences.

Students' understanding of how robotic touch sensors work is reinforced through a hands-on design challenge involving LEGO MINDSTORMS(TM) NXT intelligent bricks, motors and touch sensors. They learn programming skills and logic design in parallel as they program robot computers to play sounds and rotate a wheel when a touch sensor is pressed, and then produce different responses if a different touch sensor is activated. Students see first-hand how robots can take input from sensors and use it to make decisions to move as programmed, including simultaneously moving a motor and playing music. A PowerPoint® presentation and pre/post quizzes are provided.

Using new knowledge acquired in the associated lesson, students program LEGO MINDSTORMS(TM) NXT robots to go through a maze using movement blocks. The maze is created on the classroom floor with cardboard boxes as its walls. Student pairs follow the steps of the engineering design process to brainstorm, design and test programs to success. Through this activity, students understand how to create and test a basic program. A PowerPoint® presentation, pre/post quizzes and worksheet are provided.

This resource is a video abstract of a research paper created by Research Square on behalf of its authors. It provides a synopsis that's easy to understand, and can be used to introduce the topics it covers to students, researchers, and the general public. The video's transcript is also provided in full, with a portion provided below for preview:

"Although it might appear simple, the box jellyfish has evolved a system of vision nearly as complex as our own. The jellyfish has four sets of six eyes linked to a gravity-detecting structure known as a statolith. Inspired by this combination of natural light and gravity sensors, researchers reporting in the _Journal of Bionic Engineering _are paving the way toward improved environmental detection in robots. They’ve devised a new method for calibrating a camera linked to an inertial measurement unit, or IMU, on a robotic arm. By programming the robotic arm to spiral toward a set of visual markers during calibration, this new method produces smaller reprojection errors than popular calibration methods such as ICSR and Kalibr. Using this calibration approach, the team envisions a jellyfish-like robotic system equipped with a camera and IMU at its joints..."

The rest of the transcript, along with a link to the research itself, is available on the resource itself.

Through this unit, students act as engineers who are given the challenge to design laparoscopic surgical tools. After learning about human anatomy and physiology of the abdominopelvic cavity, especially as it applies to laparoscopic surgery, students learn about the mechanics of elastic solids, which is the most basic level of material behavior. Then, they explore the world of fluids and learn how fluids react to forces. Next, they combine their understanding of the mechanics of solids and fluids to understand viscoelastic materials, such as those found in the human body. Finally, they learn about tissue mechanics, including how collagen, elastin and proteoglycans give body tissues their unique characteristics. In the culminating hands-on activity, student teams design their own prototypes of laparoscopic surgical robots remotely controlled, camera-toting devices that must fit through small incisions, inspect organs and tissue for disease, obtain biopsies, and monitor via ongoing wireless image-taking. They use a (homemade) synthetic abdominal cavity simulator to test and iterate the prototype devices.

Students learn about the human body's system components, specifically its sensory systems, nervous system and brain, while comparing them to robot system components, such as sensors and computers. The unit's life sciences-to-engineering comparison is accomplished through three lessons and five activities. The important framework of "stimulus-sensor-coordinator-effector-response" is introduced to show how it improves our understanding the cause-effect relationships of both systems. This framework reinforces the theme of the human body as a system from the perspective of an engineer. This unit is the second of a series, intended to follow the Humans Are Like Robots unit.

Vision is the primary sense of many animals and much is known about how vision is processed in the mammalian nervous system. One distinct property of the primary visual cortex is a highly organized pattern of sensitivity to location and orientation of objects in the visual field. But how did we learn this? An important tool is the ability to design experiments to map out the structure and response of a system such as vision. In this activity, students learn about the visual system and then conduct a model experiment to map the visual field response of a Panoptes robot. (In Greek mythology, Argus Panoptes was the "all-seeing" watchman giant with 100 eyes.) A simple activity modification enables a true black box experiment, in which students do not directly observe how the visual system is configured, and must match the input to the output in order to reconstruct the unseen system inside the box.

Students act as civil engineers developing safe railways as a way to strengthen their understanding of parallel and intersecting lines. Using pieces of yarn to visually represent line segments, students lay down "train tracks" on a carpeted floor, and make guesses as to whether these segments are arranged in parallel or non-parallel fashion. Students then test their tracks by running two LEGO® MINDSTORMS® NXT robots to observe the consequences of their track designs, and make safety improvements. Robots on intersecting courses face imminent collision, while robots on parallel courses travel safely.

Students explore their peripheral vision by reading large letters on index cards. Then they repeat the experiment while looking through camera lenses, first a lens with a smaller focal length and then a lens with a larger focal length. Then they complete a worksheet and explain how the experiment helps them solve the challenge question introduced in lesson 1 of this unit.