Robotics: reading guide
Connect observations, state, maps and behavior through existing explanations and experiments.
This is an editorially selected reading order. Begin at step 1 or go directly to the topic you need.
Before you start Start with sensor, position and velocity terminology. Frames use vectors and matrices; estimation uses probability. Each topic links to its background.
1. System and runtime
Trace sensing through commands, then inspect communication and logs.
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The autonomous robot system
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ROS 2 communication
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Recording and replaying logs
Background: ROS 2 communication
- Lab · Run in browserReproduce robot failures with rosbag2: inputs, TF and time
2. Working with frames
Express the same point in different frames.
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Coordinate transforms
- Primer · Run in browserRobot coordinate transforms: matrices, quaternions and TF
3. Estimating motion and state
Distinguish integrated motion from corrections using multiple sensors.
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Wheel odometry
Background: Coordinate transforms
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IMU bias and noise
- Lab · Run in browserRead a stationary IMU log: bias, scatter and Allan deviation
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GNSS positioning and error
- Primer · Run in browserHow GNSS Works and Key Products — u-blox, Trimble, Fixposition
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Sensor fusion
Background: Frames and time · Kalman filtering
4. Registration and mapping
Explore registration failures before studying the full SLAM system.
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Point-cloud registration with ICP
Background: Coordinate transforms
- Lab · Run in browserWhy ICP fails: initialization, outliers and symmetric geometry
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LiDAR SLAM
Background: Point-cloud registration with ICP · Pose-graph update
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Evaluating SLAM accuracy
Background: LiDAR SLAM
- Lab · Run in browserHow to evaluate SLAM — ATE, RPE, runtime and failures
5. From maps to motion
Separate map representation, paths and behavior, then connect them with Nav2.
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Occupancy grids
Background: Coordinate transforms
More questions on this topic
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Path search on a map
Background: Occupancy grids
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Behavior selection
More questions on this topic