# Tag Info

9

I still think this is off-topic, but it seems I need more space than a comment to show (answer?) why that is so. You are starting from some performance specifications and are looking to get to a set of features you need in your camera. Here is a post from NI about stereo vision that gives a formula for depth resolution:  \Delta z = \frac{z^2}{fb}\...

7

Animals and robots both need to understand something about the 3D structure of the world in order to thrive. Because it's so important, animals have evolved a huge number of strategies to estimate depth based on camera-like projective sensors (eyes). Many make use of binocular disparity -- the fact that the distance between the same scene point in two ...

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

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 ...

4

Imagine someone put you in a wheelchair and blindfolded you, then let you reach your arm out and touch a wall. You could tell how far away the wall was, but as long as you were pushed parallel to the wall, how would you know how far you had gone? You can't count steps or see the end of the hall, so you do not have a way to index your samples of where the ...

3

I'll try to explain this in terms of software. Firstly, it is just next to impossible to have 100 metres (practically, 3 metres is like the best depth accuracy) and we need to be sure that the cameras are capturing images properly with all practical features (vibration-free and even under sunlight or rain)! (Else features will be lost and we end up with ...

3

Vision is actually one kind of rangefinder, although passive. Earlier camera use parallax to find the distance and focus. Nowadays, active rangefinders are developed such as ultrasonic sensors, lidar sensors, which emit a signal and checks the returned time, the time of flight. This is more accurate and could adapt to low light conditions.

3

Yes, there is such a system available today, ScenSor from DecaWave: These tags can measure their distance from base stations using the time of flight of radio packets. They have an precision of about 10cm, I.E. successive samples are randomly distributed in a 10cm diameter cloud around the true location. Also, the radio signal needs a clear line of sight ...

2

Another sensor that you should investigate is ultra-short baseline (USBL). I have used the MicronNav with success in the past. You mentioned accelerometers, but what I think you really meant is an inertial navigation system. These fuse data from accelerometers, gyros, compass, and optionally GPS for a more accurate dead-reckoning. I have used the ...

2

You could use AR markers attached to each robot or in known locations around the room. In fact, this is how it is typically done in research for indoor, multi-robot systems. The libraries for recognizing and extracting range / angle information from AR markers are well developed, and included in the Robot Operating System. Now, you won't need to actually use ...

2

I did casually search for something like this a year or two ago. "Sparse sensing" or "sensing limited" were the sort of phrases that cropped up. Kris Beevers has some interesting publications in this sort of area, such as SLAM With Sparse Sensing. His general approach was to maintain previous sensor readings while changing the direction of the robot, to ...

2

One way you can use SLAM in your setup is to stop the robot every 30 cm or so, and perform a sweep with your lidar. You can then use e.g. one of the 2D SLAM packages from openslam. The problem with sweeping while you are moving is that you cannot get any correspondence information from a single range reading. SLAM works by associating features in one ...

2

Both 1550nm and 900nm ranges are used in different lidars. Velodyne and majority others use 905nm lasers because these diodes are really cheap. 1550nm are used when there is a need for very long distance measurement range, such as Luminar, as the eye safety threshould is several orders of magnitude higher for this wavelength than 905nm. In principle, ...

2

You are correct. Most Velodyne LIDARs (very commonly used on autonomous vehicles), use 905 nm diode lasers, and so do many Hokuyo laser scanners and SICK LIDARs. A new company, Ouster, uses 850 nm lasers, claiming that their choice of lower wavelength is because the "atmospheric water absorption is orders of magnitude lower than at 905nm". Some more info: ...

2

I wouldn't recommend using sensors with different laser frequencies either, because that likely means using an entirely different product, with different accuracy and other properties. don't tilt, shift I think the idea of tilting a laser scanner is very problematic, especially with a height constraint like you have. But what about shifting the scanner up or ...

1

Short answer: They don't need. Cameras can be used as range finders, and an easy example is the Xbox Kinect. Computer vision is an area that is being studied a lot. You can find a lot on authonomous cars, and the problem of SLAM.

1

Are you sure roscore is running? "Failed to contact master" is usually an issue with roscore not initializing. If roscore indeed is running but you are still getting the message, check if ROS_MASTER_URI is set to something other than the default. Or run "rosnode list" and paste the output here.

1

So according to the datasheet from the link provided, the Data interface is indeed UART (LVTTL 3.3V). The datasheet also says it has 2 Modes of operation: Single measurement, continuous ranging 1Hz to 25Hz. The datasheet does not go into the details of the application layer (ie. the commands and structure of the data in those commands), let alone the baud ...

1

Check this, starting from the last part: I think they are using the same technology as the several of their sensors: ( the one you mentioned) In the 100 dollar price range I think you will not find anything that meets your demands. I have no experience with golf laser range finders.

1

I think 0.3m noise is a bit exaggerated for a scanning laser rangefinder. As you saw with the Hokuyo (which is one of the cheapest LIDARs you can get) they say that it is 0.03m range "error" (they do not explicitly state this is 2$\sigma$, but I have tested the noise profile myself and it is consistent with 2$\sigma$). My experience with laser scanners is ...

1

Am I exaggerating with these values? No your're not but you need to filter the measurements. Also, you can double check datasheet of any laser sensor for the specifications. I've written a code for Kalman filter long time ago for a laser sensor that measures a static point located at <10,10>. Let's see how the filter is working with the noise you've ...

1

SLAM can be done Using many different way, in this case, Yes Buddy can map around him using its sensors : RGB camera, IR sensor, Ultra sound Sensor, Encoder. The result depend of the algorithme you are using. We are also working on a 3D camera to allow buddy to have a better input of the world.

1

The core part of the HectorSLAM is in the file hector_slam/hector_mapping/include/hector_slam_lib/matcher/ScanMatcher.h and hector_slam/hector_mapping/include/hector_slam_lib/map/OccGridMapUtil.h. The implementation of the scan matching in HectorSLAM uses the maximum likelihood estimator (MLE), which is implemented in the function estimateTransformationLogLh....

1

So this is really a hard task. Estimating the position of a AUV is still a large challenge even in research. There are sensors like as DVL (Doppler Velocity Log) available that can estimate the speed over ground. These sensors working okay, but they only estimating the speed. These devices are precise enough for your use case BUT these devices are to large ...

1

Another idea is to use polarized light beacons. If you have a few light sources polarized at different angles, then you can use some simple light sensors (or cameras) similarly polarized. If the beacons are at known world locations, you should be able to figure out your location through triangulation or trilateration. the polarization lets you distinguish ...

1

An extremely cheap method would be to use IR leds mounted on your beacon and an omni-directional IR sensor array on your robot (just a few remote control leds arranged around your robot) The beacon will be glowing like a neon sign in IR and a simple brightness detection algorithm will give you a direction. Move 10cm, take another reading, etc.

Only top voted, non community-wiki answers of a minimum length are eligible