Most autonomously navigating systems depend on GPS signals to determine their position and the direction in which they should travel next. GPS, however, is not always available to serve autonomous robot navigation systems. The Institute of Electrical and Electronics Engineers, better known as IEEE, recommends a process called simultaneous localization and map building (SLAM) to supplement or, in some cases, to replace GPS signals to enhance the navigation and to promote more accurate location assessments for your systems. Visual SLAM uses a simple camera or other light sensors to provide information to your autonomous devices and to direct their movements more accurately. This process can promote the highest degree of accuracy for autonomous robot navigation systems operating in real-world environments.


The Importance of Vision 

Most of us have little or no experience of trying to navigate our environment without visual cues. Some autonomous robot navigation systems, however, are very accustomed to relying on GPS or other systems to provide information on their location without the ability to “see” their surroundings. These systems can operate effectively in environments that do not change or that do not contain any obstacles. In areas with uneven terrain or frequently shifting item placements, however, the ability to detect these changes can often be essential.


How Does Vision Work?

Obviously, the vision of autonomous navigation systems is not precisely the same as the vision of humans. A few different types of sensors are typically used to determine the surroundings and positioning of autonomous systems:

  • LiDAR sensors are considered “active”. They create detailed 3-D images of the environment by projecting lasers and receiving them with a sensor. These laser systems can estimate distances to various objects accurately and may offer panoramic ranges of view up to 360 degrees, typically done by rotating an internal mirror system to project and capture the light. New advancements in LiDAR have enabled “solid-state” LiDAR systems to be made.
  • Radar sensors are typically used to monitor blind spots and other areas to promote greater control and safety for the autonomous system. These systems are not affected by inclement weather and use short-range and long-range radio waves to
  • Ultrasonic sensors have the shortest range and deliver information about obstacles close to the autonomous robot or device. While cheap, they can be prone to noise in the data from the literal noise of the environment.
  • Infrared sensors can be a great addition to an autonomous robot for the tracking and resiliency of the sensors. Because infrared is not visible to humans, IR flashlights can be added to vehicles that need to operate in the dark without flooding the entire area with visible light. These can also be made or purchased fairly inexpensively and have a wide adoption community for development.

Along with GPS signals and the information they provide, each of these types of sensors can help your autonomous navigation system to build a 3-D image of the world around it. While your system does not “see” in the same way that a human does, it can build a virtual representation of its environment and can act on the information this representation provides to move about without running into objects in its vicinity. This allows the vision of autonomous navigation systems to serve the same purpose as the physical vision experienced by humans and animals.


Why Is Vision Important for Autonomous Robot Navigation?

Redundancy is a key ingredient to a robust navigation system. Having only GPS as your guide can fail as soon as your device drops under tree cover or experiences interference from a growing number of sources. These “GPS denied” areas can wreak havoc for your device’s sensor fusion algorithm  The addition of a vSLAM system gives your device added redundancy in the navigation to map out and follow routes even if GPS is lost. 

Additionally, a system that only uses GPS signals and the information they can provide has little chance of avoiding obstacles on the ground or in the air. This can result in damage to the robot, drone, or other autonomous system and downtime for these devices. By adding visual sensors to the mix, however, your robot or drone can enjoy the added benefits of being able to “see” the obstacles around it. This can allow even greater autonomy in avoiding damage and navigating the terrain or airspace around it more effectively.

An article published in IEEE Sensors Journal in January 2021 indicates that vision-based autonomous navigation methods offer greater flexibility in changing environments. This can increase the ability of these systems to learn and to adapt while avoiding collisions with stationary or moving obstacles.

Procedia Computer Science published an article in 2020 that outlines the various ways in which vision assists in detecting and classifying objects for autonomous vehicles and other systems. This highlights the importance of vision for autonomous navigation when safety is a significant factor.

Perhaps the most important benefit of visual sensors for your autonomous systems, however, is their ability to back up and even supersede information coming in from GPS and other systems. Your robots and drones can trust their own artificial eyes to avoid many collisions on their own. This is an essential way in which the vision of autonomous navigation systems can increase accuracy and effectiveness in real-world scenarios.


So, How Important Is Vision for Autonomous Robot Navigation?

Vision sensors and software packages are essential elements for safety-critical systems and those that will operate in unfamiliar or uneven terrain. Your robots and drones will depend on vision to provide the added information needed to navigate in GPS denied environments,l avoid obstacles, and minimize the risk of collisions in the air and on the ground. As a backup to GPS and a learning tool for intelligent systems, vision is key to achieving the best results from your autonomous devices and systems.


Inertial Sense Can Lead the Way

At Inertial Sense, we specialize in providing you with the tools and sensors you need to create autonomy and precision for a world in motion. Our precision sensors are designed to meet exacting standards for precision and effectiveness. The Inertial Sense autonomy platform makes it easy to integrate your visual sensors, software and hardware modules, and GPS into a cohesive and functional system that works for your needs. Give us a call at 1-801-691-7342 or touch base with us online to learn more about how we can help you achieve more with your autonomous navigation systems today.


Learn More:

Where is Autonomous Navigation Going in the Next 5 Years?

The Limitations of Autonomous Navigation

How Do Autonomous Robots Navigate?