robotic lawn mower

Why We Made LiDAR Mower Neomow X


Aug 01, 2023

Motivated by Market Demand

People who live overseas and own homes with attached courtyards have a strong need for lawn maintenance. Typically, there are two traditional approaches to maintaining a lawn:

  • Option 1: Hiring a professional lawn maintenance crew.
  • Option 2: Purchasing handheld mowing device and manually maintaining the lawn.

However, lawn maintenance is a seasonal and cyclical task. In most areas, users face more than six months of routine mowing in a year, sometimes even twice a week during peak plant growth. Regardless of the chosen lawn maintenance option, it presents challenges in terms of costs and effort. However, with economic development and technological innovation, the lawn mowing robot industry has emerged to address these challenges. The aim is to help users save on lawn maintenance costs and free up their time and effort invested in lawn maintenance.

Drawbacks and Restrictions of Mowing Robots that Require Perimeter Wires

Driven by market demand and technological advancements, mowing robots that require perimeter wires are starting to gain attention from the public. However, as this type of product continues to develop and become more widespread, certain issues are gradually being exposed. The main problems associated with these robots are as follows:

  • Cumbersome deployment and maintenance. Prior to use, such mowing robots require the installation of perimeter wires around the lawn, leading to higher machine learning costs. Over time, there is a risk of the perimeter wires breaking and requiring repair using a splicer, or it may need to be redeployed altogether. Additionally, due to the seasonal nature of lawn maintenance tasks, users may need to remove and store the device and deployed wires during periods when mowing is not required, resulting in the need for reinstallation when needed again.

  • Unorganized mowing model resulting in poor coverage and inefficiency. Due to technological and cost limitations, most mowing robots that require perimeter wires rely on GPS localization solutions, and some may not have any localization solutions at all. This technology does not ensure accurate positioning of the mowing robot, leading to disorganized mowing patterns and reduced coverage. Consequently, the efficiency of the robot is compromised, and the cut lawn often exhibits poor aesthetics with messy mowing marks or tire tracks.

  •  Inability to accurately avoid obstacles and lack of safety features. The majority of mowing robots that require perimeter wires lack obstacle avoidance sensors and can only detect objects through collision. This means users must pre-mark obstacles on the lawn with a perimeter wire to enable the robot to avoid them without disrupting its operation. This necessitates complex preparation for deployment and does not fully guarantee the safety of others or pets present on the lawn.

Limitations of Current No Perimeter Wire Mowing Robots

Motivated by the limitations found in mowing robots that require perimeter wires and advancements in navigation and positioning technologies, no perimeter wire mowing robots are emerging and gaining attention from users.

One crucial aspect of no perimeter wire mowing robots that has captured public interest is the navigation technology employed in these products. Currently, the market offers three major categories of mainstream navigation technology solutions, each with its own programmatic shortcomings.

1. RTK + Obstacle Avoidance Sensor (the heat solution on the market)

  • Environmental Interference

RTK positioning and navigation can be affected by environmental conditions, which may result in unstable performance across different usage scenarios. RTK solutions rely on satellite signals for positioning and navigation, utilizing dual base stations to calculate and correct coordinates. However, these solutions are highly susceptible to weather and environmental factors in the usage scenario. For instance, in scenarios with cloudy weather, heavy cloud cover, dense shade, or tall structures, the reception of satellite signals may fluctuate or even fail altogether.

The fluctuations of signal reception can result in positioning deviations that lead to inaccurate navigation, potentially causing missed or repeated mowing in specific areas of the lawn. Consequently, this leads to reduced mowing coverage and efficiency. Additionally, severe signal fluctuations can cause the device to veer off the lawn and malfunction. In certain instances, the device may fail to receive satellite signals altogether, resulting in a complete loss of position and requiring user intervention to rectify the issue.

In domestic residential scenarios, common environmental factors like shade and eaves pose challenges for the stability of the RTK solution. As a result, the automation capability of the product may be compromised in such usage scenarios. This, in turn, increases the need for user intervention and ultimately diminishes the overall user experience of the product.

  • Geographic Constraints

The distribution of satellite signals in different countries and regions can impact the stability of usage. This means that such device in certain countries and regions may experience unstable performance due to limitations in satellite signal coverage.

  • Cumbersome Deployment

The lawn mowing robot with an RTK solution requires the deployment of a base station in the usage scenario. However, this process is associated with certain challenges. The installation location of the base station must meet strict requirements, including having a strong signal reception, in order to ensure the stable operation of the device.

2. Vision Solution: V-SLAM

  • Privacy and Security

One crucial concern associated with V-SLAM solutions pertains to safeguarding user privacy. These solutions involve the utilization of cameras to gather a significant amount of image and video data from the work scene. As a result, there is a potential for direct access to the user's environmental information. It is imperative for companies to handle the protection of user's private data in a sincere and effective manner. Failure to do so may pose a risk of privacy breaches for the user.

  •  Environmental Interference

The working environment for a lawn mowing robot is predominantly outdoors, where it is exposed to various natural disturbances such as grass clippings, dust, and rainwater. These elements can potentially adhere to the camera lens during the mowing process. Due to the camera's limited viewing angle, the presence of such elements can significantly impact the acquisition of image data, resulting in decreased device stability. Additionally, the vision solution can be influenced by ambient light, causing unstable performance in brightly lit conditions.

  • Periodic Maintenance Required

As a result of the environmental disturbances mentioned earlier, it becomes necessary for users to perform regular maintenance on the camera and lawn mower device. This maintenance involves cleaning and upkeep, which ultimately increases the operational costs associated with this device.

  • Limited Mowing Area

Due to the substantial amount of image data processing required by the V-SLAM solution, it relies on the computing power of the device, resulting in limitations on the mowing area. In situations where the lawn is extensive, the device may not have the capability to cover the entire mowing area.

3. UWB+ Vision Solution

  •  Cumbersome Deployment

Likewise RTK solution, the UWB solution necessitates the installation of base stations across the lawn. To ensure comprehensive signal coverage, users are required to place base stations in specific locations following stringent guidelines. This, in turn, results in increased costs associated with machine learning and operations.

  • Heightened Maintenance Complexity

UWB base stations necessitate a consistent power source and frequent upkeep, entailing the regular replacement of batteries. This increases the operational costs associated with such products, making them more expensive to utilize.

  •  Restricted Mowing Area

The UWB solution's approach to covering the mowing area relies on deploying a higher number of base stations. However, in cases where the lawn is expansive, this deployment demands can be inconvenient for users and may not guarantee complete coverage of the entire lawn.

  • Disruption to daily life

The need to deploy additional UWB base stations to achieve extended mowing coverage can significantly disrupt the user's regular routine. The increased presence of base stations may interfere with the user's normal utilization of the lawn and hinder their overall quality of life.

Advantages of Our Solution

Neomow X offers several key advantages thanks to its navigation technology solution combining LiDAR SLAM and visual obstacle avoidance. These advantages include:

  • Reduced Environmental Constraints

The implementation of LiDAR SLAM technology in Neomow X minimises the impact of environmental factors commonly encountered during residential lawn work. Whether operating in diverse geographic areas or contending with challenging conditions such as dense shade or confined spaces under house eaves, Neomow X can operate without limitations. This versatility enables it to effectively address a wide range of usage scenarios while maintaining stable and seamless performance.

  • Easy Deployment and Operation

As mentioned earlier, the LiDAR SLAM navigation solution eliminates the need for base station signals, eliminating the requirement for users to install a base station on their lawn. Instead, a simple setup process is all that is needed to swiftly put the robot into regular operation. This not only saves users the expenses associated with using the product but also avoids any additional disruptions to their living environment.

  • Enhanced Coverage with No Missed Corners

In certain technical solutions, when conducting lawn mowing operations near corners, shrubs, and eaves, fluctuations in the base station signal may occur, resulting in reduced coverage and missed cuts in these areas. However, Neomow X is capable of maintaining stable performance even in such scenarios. It ensures comprehensive coverage of every inch of the lawn, including all corners, maximizing the overall coverage and minimizing the need for users to invest additional time and cost in secondary maintenance.

  • Suitable for Various Lawn Sizes

Neomow X is designed to cater to the diverse range of residential lawn sizes. Whether the lawn area is below 500 square meters or exceeds 3000 square meters, Neomow X is capable of providing a full coverage. This versatility ensures that Neomow X can effectively meet the needs of users, regardless of their specific lawn size.

  • Available to Install the Charging Station Indoors

One of the unique features of LiDAR SLAM is its independence from satellite or base station signals, allowing users to conveniently install the robot's charging station indoors. Despite being stationed indoors, the robot remains fully capable of autonomous operation, navigation and re-charging for lawn mowing purposes. This not only enhances the user experience but also provides added protection to the equipment, prolonging its lifespan and safeguarding the user's investment. Ultimately, this improves the product's price/performance ratio by combining convenience, device longevity, and asset protection.

  • Improved Reliability and Safety in Obstacle Avoidance System

Neomow X features multiple sensors to enhance its obstacle avoidance capabilities. It can effectively detect obstacles of various heights and types, ensuring safe avoidance. While our device also incorporates vision sensors, we have optimized their installation angle and position. Such sensors are utilized solely to enhance the performance of the algorithm and collect essential feature data while safeguarding the user's privacy. As a result, Neomow X can navigate around obstacles with flexibility, ensuring a safe user experience and providing comprehensive protection for your family.

More About the LiDAR SLAM Solution

LiDAR SLAM is a highly advanced and well-established navigation and positioning solution within the robotics industry. It is widely recognized as a mainstream technology in the field. The acronym SLAM stands for Simultaneous Localization and Mapping, representing the core functionality of this solution.

Map-building

Map-building can be defined as the process in which a robot utilizes its sensors to perceive and accurately represent the physical environment, creating a map that serves as the foundation for the robot's recognition and understanding of its surroundings. The map generated accordingly enables the robot to navigate and interact with the physical world effectively.

How the LiDAR on Neomow X Works: During the map-building process of the remotely controlled robot, the LiDAR emits detection beams that cover a 360° area around it. These beams are reflected upon encountering objects in the physical environment. The LiDAR's receiver captures these reflected beams and measures the time difference between their emission and reception. By calculating this time difference, the LiDAR determines the precise distance between the robot and the object, creating a 3-dimensional point cloud data map. This point cloud data map captures detailed characteristics of the physical environment, serving as a valuable database for subsequent robot navigation and positioning.

In addition to its mapping capabilities, Neomow X possesses the ability to update the map in real-time. When changes occur in the environment, the robot can analyse and compare the data to determine if an update to the map is necessary. By incorporating real-time updates to the map data, Neomow X achieves enhanced navigation and mowing capabilities with greater accuracy and comprehensiveness.

Positioning

Positioning, in simple terms, refers to the robot's ability to determine its location within a map by comparing the features of the actual environment with a known map.

During operation, the LiDAR on Neomow X detects environmental features in real time and compares them with data from known maps to achieve accurate positioning. Additionally, the robot continuously performs data matching, allowing for real-time positioning adjustments and calibrations whenever necessary.

To achieve independent and automated positioning, navigation, and organized mowing in a lawn, a mowing robot must pass the following two challenges:

1. Accurate Positioning

The first crucial aspect is for the robot to determine its exact location on the lawn, which aligns with the positioning capability discussed earlier. Upon powering on and activation, Neomow X autonomously collects LIDAR data and compares it with a pre-built map. Through this process, it achieves automatic self-positioning, accurately determining its location on the lawn.

2. Navigation and Path Planning

Another crucial aspect is for the robot to determine its target location and how to reach it. In the case of a lawn mowing robot, its primary objective is to cover the entire lawn effectively. This means that the robot's target location consists of a series of positions that ensure comprehensive coverage of the lawn.

Neomow X utilizes its current location and lawn characteristics to plan an efficient mowing path. It then follows this planned path from its current location to mow the lawn. In the event of encountering an obstacle during operation, Neomow X combines the target location with the direction of the planned path to navigate around the obstacle. This allows the robot to maintain task efficiency while flexibly avoiding obstacles and ensuring effective mowing operations.

Understanding Multiple Obstacle Avoidance System

Neomow X incorporates multiple obstacle avoidance strategies, focusing on three main approaches:

1. LiDAR Detection and Obstacle Avoidance

Neomow X adopts a high-precision, 360° large field of view LiDAR module. This advanced feature enables the robot to detect and locate obstacles in all directions during its operation. By accurately sensing the distribution of obstacles and swiftly determining their positions, Neomow X can efficiently plan an avoidance path in response to the detected obstacles.

2. Visual Recognition and Obstacle Avoidance

In addition to LiDAR obstacle avoidance, Neomow X incorporates visual recognition capabilities to address challenges posed by low, short, or nearby obstacles. While LiDAR primarily handles obstacle detection, the robot requires visual information to further differentiate obstacles and develop effective avoidance strategies. To accomplish this, a vision camera is positioned at the front of Neomow X. The camera dynamically captures the robot's movements and provides visual recognition of encountered low and short obstacles during operation. Based on the identified categories of these obstacles, Neomow X intelligently develops obstacle avoidance strategies. For instance, if an animal is detected, the robot will steer clear of it. If the obstacle is low or short but can be crossed safely, the robot will attempt to navigate across it, ensuring smooth mowing operation.

3. Anti-collision Bar for Additional Physical Protection

In certain situations where LiDAR or vision sensors may fail to detect obstacles, additional physical protection is crucial. The wide-angle (144°) anti-collision bar strategically placed on Neomow X serves as a last line of defence. This wide-angle anti-collision bar is positioned in the forward direction. In the event of a collision, it promptly detects the impact and triggers a response to avoid the obstacle, ensuring the safety of both the device and its surroundings.