Autonomous illuminance measurement robot system and method

Abstract

The present invention discloses an automated illuminance measurement system, comprising: a mobile robotic platform; at least one Light Detection and Ranging (LiDAR) sensor (202) mounted on the mobile robot platform; an illuminance sensor (104) mounted on the mobile robotic platform; a control system operatively coupled to the at least one LiDAR sensor (202) and the illuminance sensor (104), the control system including at least one processor and a memory storing instructions that, when executed, cause the system to: determine positional information of the mobile robotic platform based at least in part on spatial data; control movement of the mobile robotic platform within an environment based at least in part on the positional information; and associate illuminance measurement data with the corresponding positional information to generate illuminance distribution data representative of the environment.

Description

Autonomous Illuminance Measurement Robot System and Method FIELD OF THE INVENTION

[0001] The present invention relates generally to an autonomous robotic system for measuring illuminance and more particularly, to systems and methods for autonomously acquiring illuminance data within a defined operational environment. BACKGROUND OF THE INVENTION

[0002] Public lighting infrastructures are implemented to enhance pedestrian and road user safety, improve pedestrian visibility, and strengthen urban security. Such installations are required to achieve prescribed illuminance levels and uniformity ratios in accordance with applicable standards, while simultaneously optimizing energy efficiency and minimizing environmental impact.

[0003] With the increasing emphasis on sustainability and smart city development, public lighting infrastructure must balance performance requirements with reduced power consumption, lower maintenance costs, and decreased carbon emissions.

[0004] At present, outdoor illuminance measurement is predominantly conducted using manual methods. Typically, personnel deploy portable illuminance meters at designated measurement points to record lux values. This process is labor-intensive, time-consuming, and requires significant manpower, often including traffic control arrangements for measurements conducted at night. Such arrangements may disrupt normal pedestrian flow and increase operational costs. Measurement accuracy can also be affected by improper sensor positioning, angular misalignment, environmental interference (e.g., vehicle headlights, reflections, weather conditions), and human recording errors. Furthermore, the discrete and periodic nature of manual measurements does not provide continuous performance data, making it difficult to detect gradual lumen depreciation, fixture misalignment, dirt accumulation, or component failure in a timely manner. Overall, manual measurement methods are inefficient and do not readily support continuous monitoring or real-time performance assessment of lighting installations. 1 HK 30135240 A

[0005] Accordingly, there exists a need for an improved system and method capable of providing efficient, accurate, and automated measurement of outdoor illuminance.

[0006] China patent publication no. 114136439A discloses a fully automatic light measurement robot, comprising a walking mechanism, an embedded processing control main module, a motion module and a light sensor module; the embedded processing control main module includes a GPS module and a lightweight neural network computing unit. The patent application utilizes GPS positioning and a PTZ camera in combination with a lightweight neural network to recognize roads or streetlights from image signals. The route generation is based on vision-based recognition and real-time analysis of environmental features. The system relies heavily on image-based recognition, which can be adversely affected by poor lighting, weather conditions (rain, fog, snow), shadows, or occlusions, potentially reducing measurement accuracy and reliability. Further, route generation depends on GPS positioning, which may be less reliable in urban canyons, tunnels, or areas with weak satellite signals, potentially causing deviations in measurement paths. Hence, there is a need to provide an improved system and method capable of providing efficient, accurate, and automated measurement of outdoor illuminance.

[0007] Japan patent publication no. 2017026411 discloses an illuminance measurement system capable of performing measurement with a small number of people and improving measurement efficiency is provided. An illuminance measuring device having a first communication unit and being moved by a mobile device, and a position measuring unit having a second communication unit and capable of measuring a three-dimensional position of the illuminance measuring device and a data collector having a third communication unit and a storage unit in which position information data of a predetermined measurement point is stored. The data collector measuring the illuminance measured by the position measuring means. The moving device is moved to the measurement point based on the position of the measuring instrument and the position information data, the illuminance is measured by the illuminance measuring instrument, and the position of the illuminance measuring instrument at the time of illuminance measurement is determined by the position measuring means. However, the operator in the patent application is manually moves the illuminance device to each measurement point. Further, the system uses position measuring tools such as GPS instead of 2 HK 30135240 A autonomous mapping. It functions more as a position-assisted manual measurement system rather than a fully autonomous illuminance surveying solution. Hence, there is a need to provide a fully autonomous system and method capable of providing efficient, accurate, and automated measurement of outdoor illuminance.

[0008] China Patent Publication No. 118603307 discloses an automatic measuring device for indoor and outdoor environmental lighting illuminance, comprising an unmanned aerial vehicle (UAV), a wireless illuminance measuring instrument, a mobile base station, a wireless transceiver host, and a laptop computer installed with illuminance measurement data statistical calculation software. The wireless illuminance measuring instrument is mounted on the unmanned aerial vehicle, and the unmanned aerial vehicle, the wireless illuminance measuring instrument, and the wireless transceiver host are all wirelessly connected to the mobile base station via a wireless transmission network. The UAV moves to preselected measurement points, which are determined manually or externally. Therefore, the system has limited flexibility and poor adaptability to unknown or dynamically changing environments. Hence, there is a need to provide an improved system and method capable of providing high flexibility and adaptability, and automated measurement of outdoor illuminance. SUMMARY OF THE INVENTION

[0009] It is an objective of the present invention to provide a fully automated illuminance measurement system and method that optimize the overall workflow.

[0010] It is a further objective of the present invention to provide an automated illuminance measurement system and method implemented within a single, fully integrated device.

[0011] It is another objective of the present invention to provide an automatic illuminance measurement robot incorporating a LiDAR sensor configured to perform real-time spatial mapping of a measurement environment.

[0012] It is another objective of the present invention to improve measurement accuracy and repeatability through autonomous positioning and precise spatial referencing. 3 HK 30135240 A

[0013] Accordingly, these objectives may be achieved by following the teachings of the present invention. The present invention relates to an automated illuminance measurement system, comprising: a mobile robotic platform; at least one Light Detection and Ranging (LiDAR) sensor mounted on the mobile robot platform; an illuminance sensor mounted on the mobile robotic platform; a control system operatively coupled to the at least one LiDAR sensor and the illuminance sensor, the control system including at least one processor and a memory storing instructions that, when executed, cause the system to: determine positional information of the mobile robotic platform based at least in part on spatial data; control movement of the mobile robotic platform within an environment based at least in part on the positional information; and associate illuminance measurement data with the corresponding positional information to generate illuminance distribution data representative of the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The features of the invention will be more readily understood and appreciated from the following detailed description when read in conjunction with the accompanying drawings of the preferred embodiment of the present invention, in which:

[0015] Fig. 1 illustrates a top view of a mobile robot platform employed in the present invention, referred to herein as the Magni Robotic Carrier;

[0016] Fig. 2 illustrates a side view of the mobile robot platform employed in the present invention, referred to herein as the Magni Robotic Carrier;

[0017] Fig. 3 illustrates a front view of the mobile robot platform employed in the present invention, referred to herein as the Magni Robotic Carrier;

[0018] Fig. 4 illustrates a back view of the mobile robot platform employed in the present invention, referred to herein as the Magni Robotic Carrier. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

[0019] For the purposes of promoting and understanding of the principles of the 4 HK 30135240 A invention, reference will now be made to the embodiments illustrated in the drawings and described in the following written specification. It is understood that the present invention includes any alterations and modifications to the illustrated embodiments and includes further applications of the principles of the invention as would normally occur to one skilled in the art to which the invention pertains.

[0020] The present invention teaches an automated illuminance measurement system, comprising: a mobile robotic platform; at least one Light Detection and Ranging (LiDAR) sensor 202 mounted on the mobile robot platform; an illuminance sensor 104 mounted on the mobile robotic platform; a control system operatively coupled to the at least one LiDAR sensor 202 and the illuminance sensor 104, the control system including at least one processor and a memory storing instructions that, when executed, cause the system to: determine positional information of the mobile robotic platform based at least in part on spatial data; control movement of the mobile robotic platform within an environment based at least in part on the positional information; and associate illuminance measurement data with the corresponding positional information to generate illuminance distribution data representative of the environment.

[0021] The disclosed system controls movement of the mobile robotic platform within the environment, including indoor environments, outdoor environments, or mixed environments.

[0022] In accordance with a preferred embodiment of the present invention, the at least one LiDAR sensor 202 is configured to generate two-dimensional spatial data of the environment and determine positional coordinates of the mobile robotic platform.

[0023] In accordance with a preferred embodiment of the present invention, the control system is configured to determine a plurality of measurement locations within the environment and to control movement of the mobile robotic platform to the plurality of measurement locations.

[0024] In accordance with a preferred embodiment of the present invention, the measurement locations are automatically generated based on user-defined parameters including grid spacing, wall clearance or a combination thereof. 5 HK 30135240 A

[0025] In accordance with a preferred embodiment of the present invention, the control system is configured to generate a stored map of the environment prior to acquiring illuminance measurement data.

[0026] In accordance with a preferred embodiment of the present invention, the stored map is generated during a one-time mapping procedure and reused for subsequent illuminance measurement operations.

[0027] In accordance with a preferred embodiment of the present invention, the system further comprising a wireless communication module that is configured to communicate with a remote tablet device for monitoring navigation and controlling operational parameters of the robot.

[0028] The present invention also discloses a method for automated illuminance measurement using a mobile robotic platform, comprising the steps of: acquiring spatial data representative of an environment using at least one ranging sensor; determining positional information of the mobile robotic platform based at least in part on the spatial data; controlling movement of the mobile robotic platform within the environment based at least in part on the positional information; acquiring illuminance measurement data at a plurality of locations within the environment using the at least illuminance sensor 104; associating the illuminance measurement data with the corresponding positional information; and generating illuminance distribution data representative of the environment based on the associated illuminance measurement data and positional information.

[0029] In accordance with a preferred embodiment of the present invention, the determining of positional information comprises calculating two-dimensional coordinates within a mapped representation of the environment.

[0030] In accordance with a preferred embodiment of the present invention, the method further comprising generating and storing a map of the environment prior to acquiring illuminance measurement data.

[0031] In accordance with a preferred embodiment of the present invention, the storing of map of the environment comprises generating a map during a one-time mapping procedure and reused for subsequent illuminance measurement operations. 6 HK 30135240 A

[0032] In accordance with a preferred embodiment of the present invention, the method further comprising defining a measurement route comprising a plurality of measurement locations based on the stored map.

[0033] In accordance with a preferred embodiment of the present invention, the defining of the measurement route comprises automatically generating the plurality of the measurement locations based on at least one user-defined parameter and the at least one user-defined parameters incudes grid spacing, wall clearance distance, or a combination thereof.

[0034] In accordance with a preferred embodiment of the present invention, the method further comprising automatically stopping the mobile robotic platform at each measurement location prior to acquiring illuminance measurement data.

[0035] In accordance with a preferred embodiment of the present invention, the method further comprising transmitting operational data to a remote user device and receiving control commands from the remote user device. EXAMPLE

[0036] A method to operate the mobile robot platform employed in the present invention, referred to herein as the Magni Robotic Carrier 100, comprises powering on the robot and connecting it to a control device, such as an iPad, via a wireless network. The system is operated through two principal interfaces comprise a main control interface, accessible via a tablet or computer, and the robot’s onboard display. A user may access the web application once connected to the robot’s Wi-Fi. The key functions of the main control interface comprise battery status, map or LiDAR scanning status, a sidebar menu button, calibration and sensor setup, a camera 302 button, a robot control button, a window switch button, a record telemetry and video button, system settings, save-as-default map settings, remote control stick options, and a connection status indicator.

[0037] The main interface provides access to advanced configuration settings for the robot’s behavior, including linear speed and angular speed, remote control stick orientation, video streaming orientation, power operation, movement mode, and other operational parameters. The linear speed and angular speed settings allow the system to 7 HK 30135240 A adjust the robot’s movement speeds through the provided slider fields.

[0038] The method for robot remote control and measurement task execution comprises a map creation phase and a route creation phase. Prior to executing a measurement task, a pre-saved map of the operational area must be available. The system will not proceed with task execution unless a valid map has been generated and stored. During initialization, the map interface is initially empty. The robot is manually controlled using a joystick, which activates the LiDAR sensor 202 to perform real-time environmental scanning and map generation. The robot is positioned at a designated origin point of the map, and this position is assigned coordinates X = 0 and Y = 0. For optimal spatial alignment and orientation accuracy, one side of the robot’s wheels is placed flush against a straight wall or other reference surface. This ensures consistent directional alignment within the coordinate system. Once properly positioned, the robot is powered on to initiate the mapping process.

[0039] During movement, the robot’s LiDAR sensor 202 performs continuous 360- degree scanning and updates the navigation map in real time, thereby enabling autonomous path planning and obstacle avoidance. The LiDAR sensor 202 continuously acquires 360-degree distance measurements, which are processed by a simultaneous localization and mapping (SLAM) module to generate a two-dimensional occupancy grid map of the operational environment. The SLAM module estimates the robot pose in real time by correlating successive LiDAR scans and updating the map using probabilistic occupancy estimation.

[0040] The robot continues to be navigated throughout the operational area until the mapping system verifies that all predefined regions and associated physical QR code markers have been fully scanned and recorded within the system. Upon completion of the scanning process, the generated environmental map is stored in the system memory. A distinct map identifier is then entered and saved to finalize and register the map creation process.

[0041] During the route creation phase, the map must be successfully saved prior to defining any measurement route. Upon confirmation that the map has been saved, the system enables access to the measurement route configuration tools. The user activates a 8 HK 30135240 A region selection tool to define a measurement area by sequentially selecting points on the displayed map interface. Each selected point is rendered as a black node, and adjacent nodes are connected by black edges. The final selected point must connect to the first point to form a closed polygonal boundary. Upon successful closure of the polygon, all nodes and connecting edges change from black to white to indicate a valid enclosed region. If the polygon remains open, route generation will fail. The robot performs a one- time venue mapping and stores the resulting location data.

[0042] After confirming that the region is fully enclosed, route generation is initiated. The system prompts the user to input required parameters, including grid spacing and wall clearance. Grid spacing defines the distance between measurement points, while wall clearance specifies the minimum allowable distance from obstacles or walls. The procedure of activating the region selection tool and entering the required parameters may be repeated to define additional routes within the same saved map environment. Multiple routes may be generated and stored under the same map. Upon successful generation of each route, the system displays a confirmation message.

[0043] During the illuminance measurement process, the user may input and record user identification details together with the associated measurement data prior to loading the map. Thereafter, the robot is positioned in proximity to a designated QR code marker corresponding to the desired map. The vision system detects the QR code marker and, upon successful recognition, overlays a green bounding box onto the marker within the live video stream to provide visual confirmation. The robot’s current position is then synchronized with the location associated with the detected QR code. Upon successful synchronization and map loading, the system displays a confirmation message indicating completion of the process.

[0044] Prior to initiating the illuminance measurement process, the user selects an appropriate predefined route. Upon activation, the robot autonomously traverses the selected route and records illuminance readings at each designated measurement point. The robot is equipped with an illuminance sensor 104, also referred to as an illuminance meter, configured to measure lighting conditions within the operational environment. As the robot progresses along the predefined route, the grid points displayed on the map dynamically update their colour status to indicate measurement progress and completion. The system controls the robot to sequentially process all designated measurement points 9 HK 30135240 A along the selected route. Upon completion of all measurement points, the system displays a confirmation message indicating that illuminance data collection has been successfully completed.

[0045] During traversal, sensor data from LiDAR or proximity sensors is continuously evaluated by an obstacle detection module. If an object is detected within a predefined safety threshold distance along the planned path, the system transitions from an autonomous traversal state to an interruption state and generates a user notification. If an obstacle is detected during operation, the system generates a warning dialog presenting multiple response options. These options may include stopping robot movement and suspending ongoing illuminance measurement, initiating manual obstacle avoidance control, or closing the warning dialog in the case of a temporary and non-obstructive condition. Previously collected measurement data may be reviewed within the system, and reports may be generated accordingly. The reporting process includes filtering stored records, selecting specific report entries, and exporting the selected results into a desired output format.

[0046] Fig. 1-4 illustrate the mobile robot platform employed in the present invention, herein referred to as the Magni Robotic Carrier 100. The Magni Robotic Carrier 100 comprises a vision camera 302, a motor control board and a Raspberry Pi 304, and an emergency stop button 402 mounted at the back of the robot. A LiDAR sensor 202 is mounted on the top of the robot. An illuminance meter is mounted at the front of the robot for measuring lighting conditions. All operations can be monitored and controlled via a tablet through a robot monitor 102 interface.

[0047] The present invention explained above is not limited to the aforementioned embodiments, and it will be obvious to those having an ordinary skill in the art of the present invention that various replacements, deformations, and changes may be made without departing from the scope of the invention. 10 HK 30135240 A CLAIMS WHAT IS CLAIMED: 1. An automated illuminance measurement system, comprising: a mobile robotic platform; at least one Light Detection and Ranging (LiDAR) sensor (202) mounted on the mobile robot platform; an illuminance sensor (104) mounted on the mobile robotic platform; a control system operatively coupled to the at least one LiDAR sensor (202) and the illuminance sensor (104), the control system including at least one processor and a memory storing instructions that, when executed, cause the system to: determine positional information of the mobile robotic platform based at least in part on spatial data; control movement of the mobile robotic platform within an environment based at least in part on the positional information; and associate illuminance measurement data with the corresponding positional information to generate illuminance distribution data representative of the environment. 2. The automated illuminance measurement system, according to claim 1, wherein the at least one LiDAR sensor (202) is configured to generate two-dimensional spatial data of the environment and determine positional coordinates of the mobile robotic platform. 3. The automated illuminance measurement system, according to claim 1, wherein the control system is configured to determine a plurality of measurement locations within the environment and to control movement of the mobile robotic platform to the plurality of measurement locations. 4. The automated illuminance measurement system, according to claim 3, wherein the measurement locations are automatically generated based on user-defined parameters including grid spacing, wall clearance or a combination thereof. 1HK 30135240 A 5. The automated illuminance measurement system, according to claim 1, wherein the control system is configured to generate a stored map of the environment prior to acquiring illuminance measurement data. 6. The automated illuminance measurement system, according to claim 5, wherein the stored map is generated during a one-time mapping procedure and reused for subsequent illuminance measurement operations. 7. The automated illuminance measurement system, according to claim 1, wherein the system further comprising a wireless communication module that is configured to communicate with a remote tablet device for monitoring navigation and controlling operational parameters of the robot. 8. A method for automated illuminance measurement using a mobile robotic platform, comprising the steps of: acquiring spatial data representative of an environment using at least one ranging sensor; determining positional information of the mobile robotic platform based at least in part on the spatial data; controlling movement of the mobile robotic platform within the environment based at least in part on the positional information; acquiring illuminance measurement data at a plurality of locations within the environment using at least one illuminance sensor (104); associating the illuminance measurement data with the corresponding positional information; and generating illuminance distribution data representative of the environment based on the associated illuminance measurement data and positional information. 9. The method for automated illuminance measurement using a mobile robotic platform, according to claim 8, wherein the determining of positional information comprises calculating two-dimensional coordinates within a mapped representation of the environment. 2HK 30135240 A 10. The method for automated illuminance measurement using a mobile robotic platform, according to claim 8, wherein the method further comprising generating and storing a map of the environment prior to acquiring illuminance measurement data. 11. The method for automated illuminance measurement using a mobile robotic platform, according to claim 10, wherein the storing of map of the environment comprises generating a map during a one-time mapping procedure and reused for subsequent illuminance measurement operations. 12. The method for automated illuminance measurement using a mobile robotic platform, according to claim 10, wherein the method further comprising defining a measurement route comprising a plurality of measurement locations based on the stored map. 13. The method for automated illuminance measurement using a mobile robotic platform, according to claim 12, wherein the defining of the measurement route comprises automatically generating the plurality of the measurement locations based on at least one user-defined parameter and the at least one user-defined parameters incudes grid spacing, wall clearance distance, or a combination thereof. 14. The method for automated illuminance measurement using a mobile robotic platform, according to claim 8, wherein the method further comprising automatically stopping the mobile robotic platform at each measurement location prior to acquiring illuminance measurement data. 15. The method for automated illuminance measurement using a mobile robotic platform, according to claim 8, wherein the method further comprising transmitting operational data to a remote user device and receiving control commands from the remote user device. 3HK 30135240 A FIG.1 104 102 100 1HK 30135240 A 2 FIG. 2 202 HK 30135240 A 3 FIG. 3 302 304 HK 30135240 A 4 FIG. 4 402 HK 30135240 A