Three key technologies of mobile robots

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Three key technologies of mobile robots [Copy link]

There are many issues to be studied in the field of robotics, involving multiple disciplines such as computers, sensors, human-computer interaction, and biosecurity. Among them, environmental perception, autonomous positioning, and motion control are the three key issues in robotics technology. The following will discuss these three points in detail.

Environmental Perception

At present, in the robot indoor environment, the autonomous environmental perception technology of mobile robots, which is mainly based on lidar and assisted by other sensors, has been relatively mature. However, in outdoor applications, due to the variability of the environment and the influence of light changes, the task of environmental perception is relatively complex and has higher real-time requirements, making multi-sensor fusion a major technical task facing robot environmental perception.

Most of the environmental perception using a single sensor has its weaknesses that are difficult to overcome, but the effective integration of multiple sensors, through the redundancy and complementarity of information from different sensors, can almost enable the robot to cover all spatial detections and comprehensively enhance the robot's perception capabilities. Therefore, the use of lidar sensors combined with ultrasonic, depth cameras, anti-fall and other sensors to obtain distance information to realize the robot's perception of the surrounding environment has become a hot topic of research for scholars from various countries.

The use of multi-sensor environmental perception technology can bring about problems such as synchronization, matching, and communication of multi-source information. It is necessary to study methods and technologies to solve the cross-modal and cross-scale information registration and fusion of multi-sensors. However, in practical applications, the more types of sensors used, the better. For the specific application of robots in different environments, it is necessary to consider the validity of each sensor data and the real-time performance of the calculation.

Autonomous positioning

For mobile robots to achieve autonomous walking, positioning is also one of the core technologies they need to master. Currently, GPS can provide high accuracy in global positioning, but GPS has certain limitations. In indoor environments, GPS signals may be weak, which can easily lead to loss of position.

In recent years, SLAM technology has developed rapidly, improving the positioning and map creation capabilities of mobile robots. SLAM is the abbreviation of Simultaneous Localization And Mapping, which was first proposed by Hugh Durrant-Whyte and John J. Leonard in 1988. SLAM is more appropriate to be called a concept than an algorithm. It is defined as a general term for methods to solve the problem of "a robot starting from an unknown location in an unknown environment, locating its own position and posture through repeated observations of map features (such as corners, pillars, etc.) during movement, and then incrementally constructing a map based on its own position, so as to achieve the purpose of simultaneous positioning and map construction."

Path Planning

Path planning technology is also an important branch of robotics research. Optimal path planning is to find an optimal path from the starting state to the target state in the robot workspace that can avoid obstacles based on one or more optimization criteria (such as minimum work cost, shortest walking route, shortest walking time, etc.).

Depending on the degree of understanding of environmental information, robot path planning can be divided into global path planning and local path planning.

Global path planning is to plan a path for the robot in a known environment. The accuracy of path planning depends on the accuracy of environmental acquisition. Global path planning can find the optimal solution, but it requires accurate information about the environment in advance. When the environment changes, such as when unknown obstacles appear, this method is powerless. It is a kind of advance planning, so it does not require high real-time computing power of the robot system. Although the planning result is global and better, it has poor robustness to errors and noise in the environmental model.

For local path planning, the environmental information is completely unknown or partially known. It focuses on considering the current local environmental information of the robot, giving the robot good obstacle avoidance capabilities, and detecting the robot's working environment through sensors to obtain information such as the location and geometric properties of obstacles. This type of planning requires the collection of environmental data, and the dynamic update of the environmental model can be corrected at any time. The local planning method integrates the modeling and search of the environment, requiring the robot system to have high-speed information processing and computing capabilities, high robustness to environmental errors and noise, and real-time feedback and correction of planning results. However, due to the lack of global environmental information, the planning results may not be optimal, and the correct path or complete path may not even be found.

There is no essential difference between global path planning and local path planning. Many methods applicable to global path planning can also be used for local path planning after being improved, and methods applicable to local path planning can also be applied to global path planning after being improved. The two work together, and the robot can better plan the walking path from the starting point to the end point.

What is the current status of perception, positioning, and path planning technologies?

In order to solve the problem of autonomous robot walking, there are many domestic companies that conduct research on technologies such as environmental perception, autonomous positioning and path planning. As the leader in robot positioning and navigation technology, Slamtec has relatively mature products in realizing autonomous robot walking, such as Apollo, which can help companies reduce R&D costs. The Apollo robot chassis is equipped with laser ranging sensors, ultrasonic sensors, anti-fall sensors, etc. A depth camera sensor is also configured on the chassis. At the same time, with the self-developed SLAMWARE autonomous navigation and positioning system, the robot can realize autonomous mapping positioning and navigation functions.

When Apollo is in an unknown environment, there is no need to modify the environment. SharpEdgeTM refined composition technology is used to build a high-precision, centimeter-level map with ultra-high resolution and no error accumulation. At the same time, the D* dynamic real-time path planning algorithm is used to find the path and move to the designated location without secondary optimization and modification, which can directly meet people's usage expectations.

In addition, based on a pure software approach, without the need for additional auxiliary laying, Apollo can be set up with a predetermined route, or Apollo can be prevented from entering a restricted area by setting up virtual walls and virtual tracks.

When Apollo runs low on battery during operation, it can support externally scheduled scheduled charging and autonomous navigation and positioning, and automatically return to the charging dock for charging.

In addition, Apollo's expansion interface also integrates network ports, power supply interfaces and various control interfaces, so that users can quickly develop and expand. Apollo can communicate with the outside world through wired networks or WIFI. Its own battery can power itself and external expansion modules. Users can control the entire Apollo and its upper-level expansion modules through various control interfaces.

In short, in recent years, governments around the world have attached great importance to the development of robotics technology and have invested a lot of resources to stimulate robotics companies to continue to innovate and forge ahead. I believe that in the future, robots will also become an important part of people’s daily lives, leading people into a more convenient era!