Perception
Autonomous machines must perceive their surroundings without help of a human.
Antennas, radar, and Light Detection and Ranging (LiDAR) sensors detect objects around the machine.
The machine can be programmed to do tasks when it perceives one of these objects. For example, if a
sensor detects a moving object of a certain size, the machine could stop or navigate around it.
Positioning
Autonomous machines must know their position in the world as well as in their local environment.
Global Navigation Satellite Systems (GNSS) are the best way to find a machine's coordinates on a world
grid. GNSS includes the four satellite systems of GPS in the United States, BEIDOU in China, GALILEO in
the European Union, and GLONASS in Russia. GNSS requires a clear view of the sky and cannot be used
indoors. Satellite age and weather conditions affect accuracy, but cellular servers and radio base stations
could help improve it. Radio base stations near the machine get the most accurate readings, but also cost
the most.
Machines use a base location, known as an origin, when moving from one point to another. The origin is
usually a physical feature in the machine's working area. The origin is designated as (0,0) on a coordinate
grid. For example, a truck may have a nearby post as an origin acting as (0,0) on a coordinate grid, and
then the truck is programmed to move along a wall which also sits on this coordinate grid.
Machines usually need both global and local coordinate frames in order to reference objects nearby.
Global coordinates refer to its position on a map of the world, and local XY coordinates refer to the
relative position of identifiable features near the LiDAR sensor. There may be several devices mounted on
a machine that also have their own coordinate systems, and they must all align with each other.
The machine also needs a designated origin on itself. Most machines use the steering point between the
wheels as the machine's origin because there is no side-to-side (lateral) movement. Some machines do
not have a true steering point, such as machines with articulated steering.
Sometimes machines operate indoors, where obtaining GNSS data may be impossible. If indoors, Light
Detection and Ranging (LiDAR) sensors are a great alternative. If a map of the indoor space is known and
the LiDAR can detect key features, the machine could know its position based on matching the detected
features. A specific location or feature could be programmed as the origin, such as a post inside a
building, to orient the machine. Choose an origin that aligns with global North in case the machine
eventually goes outside.
Navigation
Autonomous machines must navigate from one location to another without human aid.
Machines use their origin, global, and local coordinates to know where they are. If they know where they
need to go, the machine travels from one place to another through a series of waypoints. These
waypoints could be a pre-recorded path or a series of automatically generated points determined by the
software.
Other Autonomous Requirements
Other hardware and software help the machine in moving from one location to another.
Inertial Measurement Units (IMU) are microchips that consist of gyroscopes, accelerometers, and
magnetometers. Gyroscopes detect angular velocity, accelerometers determine linear acceleration, and
magnetometers find the direction of magnetic north. However, absolute north and magnetic north are in
different locations, which need to be factored into some equations. Wheel speed sensors measure
relative motion well, but they are not good at determining global position or factoring in wheel slippage.
Antennas receive GNSS data from satellites which detect the machine's location.
The autonomy Position Filter block uses an Extended Kalman Filter mathematical equation, which fuses
all the data together to get a more accurate understanding of the position than one sensor could alone. It
records GNSS (location error), wheel odometer (speed error + angle error), and yaw source (direction
error). The output is a relative position.
User Manual
Ouster LiDAR
Introduction
©
Danfoss | March 2023
AQ404281942428en-000103 | 5
