Simplifying Autonomous Robotics: A Guide to Waypoint and Exploration Missions

Written by Raffi Jabrayan, Exyn Technologies

Often when we’re talking about autonomous robots or SLAM technology it can sound like some futuristic sci-fi jargon, but actually the technology is analogous to the same chips and code that’s in your smartphone or advanced driver’s assistance in your car. Basically, the technology that’s hard at work behind the scenes can be incredibly complex, but as the user, it works seamlessly to help you achieve your goals. 

Robotics for mapping and surveying are similar. The technology can seem complex, but the goal is to provide you with the safest and most cost-effective method to autonomously navigate and map an area with extreme precision.

That’s why when flying an autonomous mission for the first time with a platform like Nexys, it could be confusing to know which kind of mission to choose for your particular use case. On the surface, a waypoint-based or exploration-based mission might feel similar, but it changes how the robot ‘thinks’ about its mission and will help the operator know which mission mode to deploy for the most complete, and accurate 3D model. 

To get you started, we’re going to break down the differences between waypoint-based and exploration-based missions in this guide to robotic navigation.  

Waypoint-based autonomy

If you’ve ever used the renowned robot Spot from Boston Dynamics, you might be familiar with the concept of a waypoint. But you can essentially think of it as a point in 3D space, a mission objective, that we’re asking the robot to navigate towards. These waypoints are entered by a pilot or surveyor before the mapping begins. 

To understand waypoints, imagine the area you need to map is like a chessboard. Each square on the chessboard represents a possible waypoint for the robot to move to. To set your route for the robot, you select the squares or waypoints that provide the most efficient path for the robot to take. The same way you would plan a route for a chess piece to safely move across the board. However, after you press play for your autonomous mission, the Nexys will intelligently pilot the robot around any obstacles in its way. 

With aerial robots, these waypoints exist in 3-dimensions, but the concept is the same as the chessboard. However now the robot can process in three dimensions to find creative ways around obstacles. The autonomy engine that’s built into the Nexys, ExynAI, is relentless in its pursuit of mission objectives and will try to reach its waypoint multiple times before determining it’s unreachable and returning home. 

Waypoint-based autonomy missions are great tools for survey teams where they understand the environment they’d like to explore. Or if they wanted to send the robot closer to an area of interest for an inspection mission, for example. 

However, there are times when you may not be able to create waypoints or the area to be mapped has unknown features well beyond visual line of sight. For this, we pioneered a higher level of autonomy for our robots to intelligently explore a large volume of interest and select their own waypoints. 

Autonomous exploration and navigation

Autonomous exploration doesn’t use predetermined routes like waypoint navigation. Instead, the robot builds a real-time map of an unexplored area and determines its own route in real time to fully survey the given area.

The Nexys system uses autonomous exploration and achieves this through a technology known as SLAM (Simultaneous Localization & Mapping). That may sound complicated, but the technology simply mimics what humans do automatically when navigating the world around them.

Imagine you walk into a new building that you’ve never been in before. The first thing you do (without even thinking about it) is determine where you are when you first walk in. For example, you may walk into the main entrance and see the front reception desk. This is the “Localization” part of SLAM. The robot determines where it is in relation to the rest of the area.

Next, as you walk you through a building, you start making mental notes of relationships between different features. You might notice there is a stairway to the right of the front desk or a long hallway to the left. For a SLAM platform like Nexys, this is how it understands where it is in an unknown environment. It’s like spotting a familiar landmark when you’re driving and feel lost, suddenly you can reorient and know exactly where you are and how to get home. 

With exploration autonomy, the Nexys system essentially uses the same technique as you would when entering an unexplored area. Our system is constantly creating and updating a map to build a precise 3D rendition of any unexplored space. Instead of using vision like humans do, our robot uses lasers through a LiDAR sensor to ‘see’ in any condition, including zero-light areas. 

Autonomous exploration works for mapping areas in unsafe conditions or when you can’t use waypoints due to unknowns or lack of navigation signals. For example, after blasting a new mining cavity, an autonomous exploration robot equipped with our Nexys system can completely map the interior without any user input or control.

The Nexys system comes out-of-the-box with both waypoint and exploration autonomy modes so your survey teams can choose the right level of autonomy for the right job, maximizing the quality of data capture while minimizing the time needed to work on site.

How do you measure robotic autonomy?

When you read about autonomous robots, you may wonder how it is that we even evaluate the differing levels of autonomy. Different people likely have different notions when it comes to real-world autonomous performance.

For some people, a Roomba may seem fully autonomous as it navigates around their living room. For others, when they think of an autonomous robot, they imagine something from science fiction – for example, C3PO from the popular Star Wars movie franchise.

To help standardize the definitions of driverless autonomy across the automotive industry, the Society of Automotive Engineers (SAE) created an autonomy scale specifically for driverless vehicles. The levels range from 0 through 5 and each ascending level defines a higher level of autonomy.

When the engineers at Exyn released our exploration mission mode, we knew we’d need to help classify new levels of autonomy for aerial robots and modeled it after the SAE levels. The Nexyssystem is classified as level 4 autonomy which is the highest level of autonomy commercially available. An autonomous robot using waypoint-based autonomy would be classified as a level 3 autonomy. And the cruise control and advanced driverless features you use in your car are commonly defined as level 2 autonomy.  

Level 5 represents the ultimate goal of robotics and defines complete and extended autonomy in any situation. Using our previous example, the C3PO character from Star Wars would be classified as level 5 using the SAE scale. As of today, level 5 autonomy is not yet available for any commercial application.

We hope this guide helped you better understand how waypoint and autonomous expiration work in the real world. The Nexys system offers both methods of navigation, so you have the flexibility to approach any mapping situation.

Contact us today to book a demo of the Nexys platform and experience the speed, safety, and cost savings that our advanced mapping technology can bring to your organization.