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How Are Visual SLAM And LiDAR Used In Robotic Navigation?


Since technological advancements have had their fair share of exposure, several high-profile movies and documentaries have demonstrated them. One such profile is visual SLAM and LiDAR. While some geeks may know what a LiDAR is through action movies, it is different from what is shown. Such a system came into existence when navigation found its way to the robotic application. For any robotic application, a navigation system plays a significant role, helping robots sense and map the environment around them to manoeuvre effectively.

Such an activity requires a motion sensor. However, this might not always be the case; people may use an inertial measurement unit (IMU) to pair with specific software to generate a robot map. Simultaneous Localization and Mapping systems or SLAM is yet another system that determines a robot’s position and orientation by developing a map while tracking the robot’s movement within the designed environment. It is essential to know that one of the most standard SLAM applications depends on optical sensors – LiDAR (Light Detection and Ranging) and visual SLAM (VSLAM, based on cameras), utilizing 2D or 3D scanners.

Simultaneous Localization and Mapping systems or SLAM is yet another system that determines a robot’s position and orientation by developing a map while tracking the robot's movement within the designed environment. #robot #robotics Click To Tweet


The inertial measurement unit guides a laser navigation robot vacuum and enables it to get back on track after getting blocked by obstacles. However, you can integrate such a measurement unit with either LiDAR or visual SLAM to create a more considerable solution. Keep reading to know how these approaches and methods differ from each other.

What Is LiDAR & How Does It Function?

A LiDAR-based SLAM application utilizes laser sensors connected with an IMU to create a room’s map. This is quite similar to that of visual SLAM. But, such a system moves further by working through a more significant precision in one dimension. LiDAR tends to estimate the distance to a wall or chair leg by illuminating a specific object with various transceivers. Here, every transceiver emits pulsed lights, which allows the system to measure the reflected pulses. This happens to calculate the distance and position of objects.

Since the light travels with a considerable speed, you require a precise and accurate laser performance to track a robot’s distance from each of its targets. Such an amount of precision makes LiDAR an accurate and fast approach. However, this is only applicable to what it sees through the map. Various other factors can affect a robot’s movement.


The Downside

A 2D LiDAR often used in standard robotic applications does not map objects that occlude with another placed at LiDAR’s height. Moreover, if the object has an irregular shape and does not follow the same width, the information provided to the robot’s system is lost.

What is Visual SLAM & How Does It Function?

A visual SLAM system utilizes a camera, often partnered with an IMU, to plot and map a robot’s navigation path. Remember, when the system uses an IMU with visual SLAM, one can refer to it as VIO or Visual-Inertial Odometry. Meanwhile, odometry refers to the motion sensor data for calculating a robot‘s positional changes. While you can perform the SLAM navigation indoors and outdoors, the more standard way of utilizing such a robotic system is indoors.

In visual SLAM systems, set points determined by algorithms get tracked through several constant camera frames. Such a process occurs to triangulate a robot’s 3D positions, often referred to as feature-point triangulation. Another notable fact about the system is that this information bounces or relays back to develop a 3D map and locate the robot’s position.


After the localization and mapping processes through SLAM are complete, a robot can calculate and chart its navigation path. With the visual SLAM, robotic vacuum cleaners can efficiently navigate the space without getting obstructed by coffee tables or chairs. This is because it can figure out its location along with the surrounding subjects.

The Downside

One of the potential errors you will face in the system is the reprojection error, which happens to distinguish between the perceived location of the actual setpoint and each setpoint.

How To Select A Suitable Navigation Method?

While making your mind on which navigation systems to utilize in the robotic application, it is essential to know the common challenges. As already discussed, robots have to navigate through various routes and surfaces. For instance, a robotic cleaner has to navigate tiles, rugs, hardwood and locate an ideal course between different rooms. While choosing the navigation system, understand the location-based data and how a robot requires it to understand an environment’s common obstacles.

The Bottom Line


Both LiDAR and visual SLAM can take care of such challenges. While LiDAR is much more accurate, faster, but costly, visual SLAM is cost-effective and can be utilized through inexpensive equipment. Moreover, a visual SLAM system can also leverage a robot’s 3D map. However, it is not so precise and turns out to be a fraction slower than LiDAR.

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