# Tag Info

15

The Roomba solution to this problem was to add cliff sensors, which are really just downward facing proximity sensors: Although this technique seems to have problems with some surfaces, such as dark tile floors, it sounds like this won't be a problem for your application. You can even make one yourself with an IR LED and an IR photo diode, for example this ...

10

If permanent magnets are rigidly mounted at a fixed distance from the IMU, they have no effect on the accelerometers and gyros inside the MPU-6050. You can optionally connect the MPU-6050 to an external magnetometer. (It's used to cancel out yaw drift). That magnetometer, if you have one, will be affected by magnets. In theory you could shield the ...

9

First I would question your math that got you to the 12b sensor. If you have a $dy$ of 1 mm over an arm that is $r = 1$ m long, then $\sin(\theta) = dy/r \rightarrow \theta = \mbox{asin}(dy/r)$. If you make the small angle approximation $\sin{\theta} \approx \theta$, then $\theta \approx dy/r$. This is $\theta$ in radians, so you're looking at a full ...

8

The processor has to execute something. You will always have an "endless" loop even if you're doing some work in an interrupt handler. The best solution depends on exactly what you're trying to do. The main advantage of using interrupts is they allow you to service events in real-time while your main program is doing something else. Timer interrupts ...

8

You might try a simple microphone. They're available in tiny surface mount packages: You'll need to rub it across the surface, and you should be able to recognise different surface textures by the sound they make. Do a Fourier transform on it, and you should be able to tell something about the scale of the surface textures. You might not want to rub the ...

8

The only way to get a velocity from an accelerometer is to numerically integrate the output of the accelerometer. That is, $$v = v_0 + a*dT \\$$ where $dT$ is the elapsed time between accelerometer readings. This means that you need to find the initial velocity $v_0$, and that an accelerometer cannot give an absolute velocity reading, only relative. ...

7

An easy and cheap approach is to use a a touch sensor like a whisker. The controller just monitors whether the whisker is in contact with the ground, if one is not then it stops and moves away from that wisker. Another fairly cheap method is to use a set of IR range finders pointed toward the ground. The controller then monitors the values returned from the ...

7

A combination of a passive infrared detector (PIR) and sonar range finder (SRF) should do the trick. What has worked well for me previously (not finding humans but very similar) was to have two PIRs on the left and right sides pointed so they have a little bit of overlap in the middle. You can then figure out if the human is to the left, right or in front ...

7

The following diagram (1) illustrates a method by which a Lancaster navigator determined airplane height above the water of a lake. Such a method is useful if the ground lacks features needed for other forms of Visual Servoing. A program I saw about mission Chastise showed one spotlight shining green and the other red, to avoid confusion about which way to ...

7

The sound beam is not traveling in a straight line but is leaving the range finder is a multi-lobed pattern. Of course we are interested in the main lobe. When the sound wave hits an object, it is reflected in various directions. So some of that energy returns to the sensor and triggers it, therefore measuring the distance. Reflection depends on the ...

7

FWIW, I once needed to create a plexiglass window/shell for a near-IR camera. Most CCD and CMOS sensors are sensitive in the near IR range (e.g. around 850nm), which is where @user3095849 suggested your sensor sits. I went to a local plexiglass supplier and asked for samples of various sheets (they often have lots of leftover pieces) and simply tried them ...

6

There are numerous options that could/should work here. As mentioned by Elias, an IR sender/receiver is a good choice. This is similar to a "break beam" sensor. Essentially, when the beam of light between the transmitter and receiver is broken, the controller knows to do something about it. Similar to this would be an IR distance sensor, which records the ...

6

Using a so-called optical flow sensor is the best way to help with holding the horizontal (i.e. in X-Y plane) position. I don't see any reason why you couldn't do the same for vertical control, although a sonar is probably easier and cheaper to use for this (likewise, if you are indoors, you could use 2 sonars for the horizontal position as well) People ...

6

The answer is that 3-axis accelerometers don't have a left handed coordinate system just for the gravity. In static condition (i.e. if the accelerometer is not accelerating with respect to any inertial frame) they measure the opposite of gravity acceleration, not the gravity acceleration itself. In more general terms, the accelerometers measure the ...

6

In short, what you are trying to do is well beyond the capabilities of top robotics research labs. That said, here is a short list of general areas you need to look into: Robotic arm dynamics (to swing the racket) Vision processing to track the shuttle Shuttle dynamics to predict shuttle path (this is not well studying so you would most likely have to ...

6

First you need to know the wavelength of the sensor. According to the sharp sensors datasheet for GP2Y0A21YK, the cover should efficiently transmit light throughout the wavelength range of the LED(λ = 850 nm ± 70 nm). Second you need to find the exact material which can transmits the wavelength of the sensor. Some transparent plastics such as acrylic glass ...

6

Localization under water was always a problem in ocean robotics as electromagnetic signals do not propagate very well in water. I think your best localization sensor in that case would be the good old sonar, which works much faster in water. You could have four of them and detect how far are the pool walls on each side then with a triangulation algorithm ...

6

There are lots of ways to solve this problem, which falls into the category of Control Engineering. There are two standard approaches: Classical Control: The control command has to be proportional to a linear combination of the error, the rate of change of the error, and the integral over time of the error, a.k.a. a PID controller. This approach ...

6

Let's recall that sensors are used to measure a physical quantity. The distinction between passive and active sensor characterize the sensor ability to retrieve a measurement without or with inputing energy (mechanic or electromagnetic or else) in the environment. For example, an infrared proximity sensor is active because the sensor needs to actively emit ...

6

There isn't really a relationship between them, unless you're asking how the dynamics feed each other when combined into a system. If that's the case, then I would suggest maybe starting with a review of the Luenberger observer. It's typically taught as the "dual" of the state feedback control problem - state feedback controls attempt to drive the system ...

5

With a series of planetary gear sets aligned axially, one can gear down by high ratios. For example, the picture below (a wikipedia commons image used in the planetary gear article) shows a 2.5-cm gearset with ratio -5/352, about 1:70. Stacking three of these would give a ratio of about 1:343000. Some torque and power would be lost to friction, and ...

5

What you're looking for is generally referred to as a slip ring. Here's a cheaper slip ring sold by Adafruit along with a video demonstrating how it works: http://www.adafruit.com/products/736. They sell hobbyist parts. I've used slip rings before to manufacture my own rotating LiDAR using a Hokuyo. Here's another company that sells what seem to be ...

5

Assuming your vehicle is roughly horizontal to the ground, you won't be able get a good estimate of yaw from the accelerometer. Consider the nominal case: when your accelerometer is pointing straight down (Ax=0, Ay=0, Az=g) the reading will never change as you change yaw angle. Normally, to get yaw angle vehicles use a magnometer (measure earth's magnetic ...

5

My favorite is the Learning OpenCV book. It has a fantastic stereo / 3D section that introduces concepts from the ground up. If you're at a university, you might be able to find the digital version available from the library website. Depends, especially on how you are going to combine scans into a full 3D pointclound (if you need 360 degree views.) ...

5

Honestly it depends what you want, I will cover some options from cheapest to most expensive Ultrasonic sensor on a servo 5-50$depending on the model. It can be fairly accurate with around 1cm accurcy and 255 steps on a full circle, but it can have poor performance in dusty environments and can have poor results with curved items. Ir distance sensor, 10-... 4 From Microsoft site: What's the difference between the Kinect for Windows sensor and the Kinect for Xbox 360 sensor? The Kinect for Windows sensor is a fully-tested and supported Kinect experience on Windows with features such as “near mode,” skeletal tracking control, API improvements, and improved USB support across a range of Windows computers and ... 4 I know this is an old question but I will just add a bit to the currently existing answers. First, this is a very complex problem that everyone is trying to tackle, including google with their Tango project. In general, to localise indoor you either need to rely on your internal sensors, or get assistances from a indoor infrastructure deployed to assist you ... 4 There are a number of different approaches to solving this problem: Distance Sensors Touch Sensor RFID Tags around the edge of the table (Or magnets) Camera (Using image processing, would be harder and the arduino would probably not be powerful enough for this) With the distance sensor you will need to check whether it is a digital or analogue signal ... 4 OK. I'm too lazy to read the document, but in general you can model the sensor response as $$\alpha_m = S \alpha + b$$ where$\alpha$is the actual acceleration in three dimensions with respect to the accelerometer body (including the acceleration due to gravity),$\alpha_m$is the measured acceleration from the accelerometer,$b$is an offset, and$S\$ is ...

4

I recommend arranging your sensors like the following: Thickness of Line <--------> /\ | | / \ | * * | || | | || moving * | | * || direction | | || | * * | ...

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