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Lecture 6: Geometric Perception (part 1)

russtedrake

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Geometric perception

(part 1)

MIT 6.881: Robotic Manipulation

Fall 2020, Lecture 6

Follow live at https://slides.com/russtedrake/fall20-lec06/live

(or later at https://slides.com/russtedrake/fall20-lec06)

So far, we have assumed a "perception oracle" that could tell us \(X^O_W\).

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Stop using "cheat ports"

Use the cameras instead!

Geometry sensors -- lidar / time of flight

Velodyne spinning lidar

Hokoyu scanning lidar

Luminar

(500m range)

Geometry sensors -- stereo

Carnegie multisense stereo

Point Grey Bumblebee

Geometry sensors -- structured light

Microsoft Kinect

Asus Xtion

https://arxiv.org/abs/1505.05459

Geometry sensors -- time of flight

Microsoft Kinect v2

https://en.wikipedia.org/wiki/Time-of-flight_camera

Samsung Galaxy DepthVision

Geometry sensors -- projected texture stereo

Intel Realsense D415

Our pick for the "Manipulation Station"

Major advantage over e.g. ToF: multiple cameras don't interfere with each other.

(also iPhone TrueDepth)

from the docs: "Each pixel in the output image from depth_image is a 16bit unsigned short in millimeters."

two on wrist

Real point clouds are also messy

figure from Chris Sweeney et al. ICRA 2019.

to the "whiteboard"...

https://forms.gle/dY6UPSXyE4gmLAQR7