A dynamic parallel weeding robot remote control system
By using a dynamic parallel remote control system for weeding robots, combined with LoRa communication and multi-sensor modules, the energy waste and safety issues of existing weeding robots under environmental changes are solved, achieving precise weeding and remote control, and improving the system's automation and safety.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HENAN UNIV OF SCI & TECH
- Filing Date
- 2026-01-22
- Publication Date
- 2026-06-05
AI Technical Summary
Existing weeding robots suffer from problems such as energy waste, inaccurate positioning, and inability to be remotely controlled during environmental changes and operation. Furthermore, they lack safety and stability in harsh environments.
The system employs a dynamic parallel weeding robot remote control system, which combines LoRa communication technology and multi-sensor modules to achieve real-time data acquisition and processing. The control process is optimized through a central control unit, integrating image recognition and path planning, and equipped with a lightning protection module to ensure safety.
It enables automated and unmanned management of weeding robots, improves operational efficiency and safety, reduces resource waste and economic losses, and supports remote monitoring and precision weeding.
Smart Images
Figure CN122151620A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of remote control technology for weeding robots, specifically a remote control system for a dynamic parallel weeding robot. Background Technology
[0002] Most existing weeding robots are operated manually, which is cumbersome and labor-intensive. Ordinary control systems have relatively simple internal processes. With the development of intelligent agricultural machinery, weeding robot designs with intelligent remote control systems have emerged, such as dynamic parallel robot weeding systems. These systems identify, locate, and remove weeds using lasers. However, they do not consider the impact of external environment and their own performance during operation, resulting in significant energy consumption and waste of human and material resources. Furthermore, they cannot accurately locate the robot's trajectory, requiring manual control for short distances, and cannot remotely control long-distance areas.
[0003] The development of a purely electric-driven weeding robot for hilly orchards by Huang Xuekai et al., while demonstrating good performance in the hilly orchard environment, still has some limitations. First, the research did not fully consider the impact of changing environmental conditions on robot performance: in high-temperature environments, the electric robot's battery poses certain safety hazards; while in low-temperature conditions, the battery's endurance decreases significantly, limiting the robot's application range and promotion potential. Second, although a modular layout is adopted to enable rapid battery replacement, the lack of external shielding for the battery means that safety and stability during rainy weather operations still need further optimization. A weeding robot control system and method invented by Wang Yi et al. of Chongqing University of Technology only controls the vehicle to perform weeding by constructing a map. It does not collect online data on the robot's environment and operation process, nor does it achieve remote control.
[0004] Galatai et al. from Inner Mongolia University of Technology invented a control method and system for weeding robots suitable for photovoltaic environments. The system uses a multi-sensor obstacle avoidance module to collect obstacle data and construct a three-dimensional obstacle map to achieve autonomous operation. However, the system's operating environment was not tested, and it did not achieve autonomy or unmanned operation. After encountering a malfunction, manual operation is required. Summary of the Invention
[0005] To address the problems existing in the prior art, the purpose of this invention is to provide a remote control system for a dynamic parallel weeding robot.
[0006] The technical solution adopted in this invention is: a remote control system for a dynamic parallel weeding robot, including a deployment unit and a disarming unit. The deployment unit is electrically connected to an external environment acquisition module via wires. The information acquired by the external environment acquisition module is transmitted to the central control unit via a LoRa communication unit. One of the control signals of the central control unit is output to the weeding control unit via serial communication. The weeding control unit is connected to the intelligent weeding operation unit and the weeding point unit via wires. The intelligent weeding operation unit is connected to the weeding speed monitoring unit via wires. The central control unit outputs two additional control signals to the signal processing unit and the image recognition unit, respectively. The signal processing unit is connected to the platform display unit via a network, and the platform display unit is connected to the human-machine interface unit via a wire. The human-machine interface unit is electrically connected to the disarming unit via a wire. The image recognition unit is electrically connected to the path planning unit via a wire, and the path planning unit is electrically connected to the weeding unit via a wire.
[0007] As a preferred embodiment, the external environment acquisition module includes a voltage acquisition unit, a temperature and humidity sensor, a smoke sensor, a light sensor, a water immersion sensor, a power detection unit, a GPS positioning unit, a surge protector unit, a fault detection unit, and a speed detection unit.
[0008] As a preferred embodiment, the external environment acquisition module also includes a data processing unit, a data collection unit, and a data integration unit.
[0009] As a preferred embodiment, the voltage acquisition unit, temperature and humidity sensor, smoke sensor, light sensor, water immersion sensor, power detection unit, GPS positioning unit, surge protector unit, fault detection unit, and speed detection unit input the collected data to the data processing unit. The data processed by the data processing unit then passes through the data collection unit and the data integration unit before being output to the LoRa communication unit.
[0010] As a preferred embodiment, the Lora communication unit uses Lora nodes to upload their real-time data to the Lora master node, and uses WiFi communication to upload the data collected by the Lora master node to the cloud platform, thereby enabling the control and monitoring of the weeding robot through the cloud platform.
[0011] The beneficial effects of this invention are: To address the shortcomings of existing technologies, this solution provides a remote control system for a dynamic parallel weeding robot. By optimizing the control system's composition, the following technical effects can be achieved: This solution utilizes LoRa communication technology to achieve real-time data transmission of the dynamic parallel weeding robot's operation; LoRa communication technology ensures the safe and efficient operation of the dynamic parallel weeding robot system; the system enables offline remote monitoring, truly realizing automated, scientific, unmanned, and integrated management of the dynamic parallel weeding robot, thereby achieving precise weeding through rational statistics and analysis; the dynamic parallel weeding robot system is simple and practical to operate. Furthermore, it addresses current weeding systems with comprehensive alarm functions, immediately alerting and handling any problems to minimize economic losses. Attached Figure Description
[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0013] Figure 1 This is a schematic diagram of the modules of the robot remote control system; Figure 2 This is a schematic diagram of the communication components in the robot remote control system. Figure 3 This is a schematic diagram of the external data acquisition part in the robot remote control system. Detailed Implementation
[0014] The present invention will now be described in detail through exemplary embodiments. However, it should be understood that, without further description, elements, structures, and features in one embodiment may be advantageously incorporated into other embodiments.
[0015] It should be noted that, unless otherwise defined, the technical or scientific terms used herein should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains; the words "a," "an," or "the" and similar terms used in the patent application specification and claims of this invention do not express a quantity limitation, but rather indicate the presence of at least one; the words "comprising" or "including" and similar terms indicate that the elements or objects preceding "comprising" or "including" cover the elements or objects listed following "comprising" or "including" and their equivalents, but do not exclude other elements or objects having the same function; The following is in conjunction with the appendix Figure 1-3 The specific components of a remote control system for a dynamic parallel weeding robot are described below: like Figure 1 As shown, a remote control system for a dynamic parallel weeding robot mainly consists of a deployment unit 1, an external environment acquisition module 2, a LoRa communication unit 3, a central control unit 4, a signal processing unit 5, a platform display unit 6, a human-machine interaction unit 7, a disarming unit 8, a serial communication unit 9, a weeding control unit 10, a weeding intelligent operation unit 11, a weeding positioning unit 12, a weeding speed detection unit 13, an image recognition unit 14, a path planning unit 15, and a weeding unit 16. Both the deployment unit 1 and the disarming unit 8 are connected to the central control unit 4 via wires. The deployment unit 1 serves to detect the overall safety of the system, and its I / O ports are connected to the I / O ports in the central control unit 4. The GND terminal in the deployment unit 1 is connected to the GND terminal in the central control unit 4. The terminals are interconnected. The external environment acquisition module 2 transmits the collected information to the central control unit 4 in real time through the LoRa communication unit 3. One control signal of the central control unit 4 is output to the weeding control unit 10 through the serial communication unit 9. The weeding control unit 10 is connected to the weeding intelligent operation unit 11 through wires. The other five control signals of the central control unit 4 are output to the signal processing unit 5, the human-machine interaction unit 7, the weeding positioning unit 12, the weeding speed detection unit 13, and the image recognition unit 14, respectively. The signal processing unit 5 is connected to the platform display unit 6 through the network. The image recognition unit 14 is electrically connected to the path planning unit 15 through wires. The path planning unit 15 is electrically connected to the weeding unit 16 through wires.
[0016] In this embodiment, the RX, TX, GND, and VCC terminals of the LoRa communication unit 3 and the RX, TX, GND, and VCC terminals of the central control unit 4 are interconnected. The RX, TX, GND, and VCC terminals of the central control unit 4 are connected to the RX, TX, GND, and VCC terminals of the signal processing unit 5 via wires. The SCL, SDA, GND, and VCC terminals of the central control unit 4 are connected to the SCL, SDA, GND, and VCC terminals of the human-machine interaction unit 7 via wires.
[0017] In this embodiment, the RX, TX, GND, and VCC terminals in the central control unit 4 and the RX, TX, GND, and VCC terminals in the image recognition unit 14 are interconnected to acquire images. The image recognition unit 14 and the path planning unit 15 are connected by wires. Path planning achieves the shortest path for weed removal. The path planning unit 15 and the weeding unit 16 are connected by wires to remove weeds.
[0018] In this embodiment, the RX, TX, GND, and VCC terminals of the central control unit 4 are connected to the RX, TX, GND, and VCC terminals of the serial communication unit 9 via a serial port. The serial communication unit 9 sends command signals to the RX, TX, GND, and VCC terminals of the weeding control unit 10 through its RX, TX, GND, and VCC terminals. The weeding control unit 10 sends commands to the intelligent operation unit 11 to enable the trolley to operate intelligently. It is interconnected with the IO, GND, and VCC ports of the central control unit 4 and the IO, GND, and VCC ports of the weeding speed monitoring unit 13 to realize real-time speed monitoring of the trolley.
[0019] In this embodiment, temperature and humidity sensors are used to collect data on the surrounding environment. If the values are higher than the system's preset values, the weeding machine will not operate. A water immersion sensor is used to detect rain; if the required rain conditions are met, the weeding equipment will also not operate. The system can also detect smoke, water immersion, and the environmental conditions around the machine's current operation. Hall effect sensors are used to detect the robot's speed, and GPS displays the robot's location in real time, allowing for path tracking. Most importantly, power sensors are used to detect the voltage and current of all electrical equipment, enabling real-time power consumption monitoring and improving system reliability and stability, thereby addressing resource constraints.
[0020] In addition, a surge protection module has been added to the control system. When encountering high voltage and high current, it can effectively ensure the safety of the system. It also has a full range of alarm functions, and can immediately alarm and handle problems, minimizing economic losses. Only the surge protection module needs to be replaced, reducing the economic losses to the machinery and equipment caused by high voltage and high current.
[0021] During the robot's weeding process, a camera is used to take pictures, and the YOLO algorithm is used to distinguish between weeds and Chinese medicinal herbs. The path planning algorithm is used to achieve the shortest distance weeding, which greatly improves work efficiency and reduces power consumption.
[0022] like Figure 2As shown in the figure, this is the communication component of the control system described in this invention. It can be seen from the figure that LoRa nodes upload real-time data to the LoRa master node, thereby connecting the RX, TX, GND, and VCC terminals of the LoRa master node with the RX, TX, GND, and VCC terminals of the main microcontroller. The LoRa master node primarily solves the problem of long-distance communication. The RX, TX, GND, and VCC terminals of the main microcontroller are connected to the RX, TX, GND, and VCC terminals of WiFi to display data. At this time, the data collected by the LoRa master node can be uploaded to the cloud platform via WiFi. The cloud platform can display temperature, humidity, smoke content, light intensity, and whether water immersion has occurred. It can also detect the voltage, current, and power usage of each electrical appliance, display latitude and longitude, monitor speed using speed sensors, and remotely control terminal devices. This allows for individual and simultaneous control of robots and vehicles, improving system safety. The cloud platform also enables the control and monitoring of robots.
[0023] like Figure 3 As shown, the external environment acquisition module 2 mainly consists of a voltage acquisition unit 201, a temperature and humidity sensor 202, a smoke sensor 203, a light sensor 204, a water immersion sensor 205, a power detection unit 206, a GPS positioning unit 207, a surge protector unit 208, a fault detection unit 209, a speed detection unit 210, a data processing unit 211, a data collection unit 212, and a data integration unit 213. The voltage acquisition unit 201, temperature and humidity sensor 202, smoke sensor 203, light sensor 204, and water immersion sensor 205... The data collected by the power detection unit 206, GPS positioning unit 207, surge protector unit 208, fault detection unit 209, and speed detection unit 210 are transmitted in real time to the data processing unit 211. The data processing unit 211 transmits the processed data to the data collection unit 212, and then to the data integration unit 213. The data integration unit 213 transmits the integrated data to the LoRa communication unit 3. The data collected by each sensor is calculated and processed by the controller, and then wirelessly transmitted to the LoRa master node using LoRa communication.
[0024] In this embodiment, the SCL, SDA, GND, and VCC terminals of the voltage acquisition unit 201 are interconnected with the SCL, SDA, GND, and VCC terminals of the central control unit 4; the SCL, SDA, GND, and VCC terminals of the temperature and humidity sensor 202 are connected to the SCL, SDA, GND, and VCC terminals of the central control unit 4; the ADC, GND, and VCC terminals of the smoke sensor 203 are interconnected with the ADC, GND, and VCC terminals of the central control unit 4; the ADC, GND, and VCC terminals of the light sensor 204 are interconnected with the ADC, GND, and VCC terminals of the central control unit 4; and the ADC, GND, and VCC terminals of the water immersion sensor 205 are interconnected with the central control unit 4. The C, GND, and VCC terminals are interconnected with the ADC, GND, and VCC terminals in the central control unit 4. The SCL, SDA, GND, and VCC terminals in the power detection unit 206 are interconnected with the SCL, SDA, GND, and VCC terminals in the central control unit 4, allowing for monitoring of the power consumption of each appliance and thus saving electricity. The RX, TX, GND, and VCC terminals in the GPS positioning unit 207 are connected to the RX, TX, GND, and VCC terminals in the central control unit 4. The GND and VCC terminals in the surge protector unit 208 are interconnected with the GND and VCC terminals in the central control unit 4, providing protection against high current and high voltage. The IO port, GND, and VCC of the fault detection unit 209 are interconnected with the IO port, GND, and VCC terminals in the central control unit 4. The speed detection unit 210 detects the vehicle's speed through the RX, TX, GND, and VCC terminals in the central control unit 4. The data processing unit 211 transmits the processed data to the data collection unit 212 via wires. The data collection unit 212 then integrates the data with the data integration unit 213 via wires. The integrated data is then transmitted to the main LoRa communication unit 3 via the RX, TX, GND, and VCC terminals.
[0025] Current research on field weeding using traditional Chinese medicine is limited. Most methods rely on image recognition for weed identification and laser weeding. However, laser weeding suffers from several drawbacks: it requires significant electrical energy, leading to high costs; it lacks path planning during operation, resulting in resource waste; and most importantly, it fails to monitor equipment safety during operation. This research addresses these issues by employing intelligent weeding technology, which overcomes the resource waste and reduces costs associated with laser weeding. Path planning enables precise weeding, saving resources and time. Crucially, environmental monitoring minimizes safety risks during machine operation, and the LoRa module allows for long-distance detection and control. To enhance system safety, a pluggable surge protector module is used. In the event of a high current, high voltage, or extreme environmental impact, the surge protector module is damaged first, causing system shutdown. Before restarting the system, simply replace the surge protector module.
[0026] It should be noted that although the present invention has been described through the above embodiments, the present invention may have many other embodiments. Without departing from the spirit and scope of the present invention, those skilled in the art can obviously make various corresponding changes and modifications to the present invention, but all such changes and modifications should fall within the scope of protection of the appended claims and their equivalents.
Claims
1. A remote control system for a dynamic parallel weeding robot, comprising a central control unit (4) and a deployment unit (1) and a disarming unit (8) connected to the central control unit (4) via wires, characterized in that: The information collected by the external environment acquisition module (2) is transmitted to the central control unit (4) in real time through the Lora communication unit (3). One of the control signals of the central control unit (4) is output to the weeding control unit (10) through the serial communication unit (9). The weeding control unit (10) is connected to the weeding intelligent operation unit (11) through wires. The control signals of the central control unit (4) are also output to the signal processing unit (5), the human-machine interaction unit (7), the weeding positioning unit (12), the weeding speed detection unit (13), and the image recognition unit (14), respectively. The signal processing unit (5) is connected to the platform display unit (6) via a network. The image recognition unit (14) is electrically connected to the path planning unit (15) via a wire. The path planning unit (15) is electrically connected to the weeding unit (16) via a wire.
2. The remote control system for a dynamic parallel weeding robot according to claim 1, characterized in that: The external environment acquisition module (2) includes a voltage acquisition unit (201), a temperature and humidity sensor (202), a smoke sensor (203), a light sensor (204), a water immersion sensor (205), a power detection unit (206), a GPS positioning unit (207), a surge protector unit (208), a fault detection unit (209), and a speed detection unit (210).
3. The remote control system for a dynamic parallel weeding robot according to claim 1, characterized in that: The deployment unit (1) is used to detect the overall security of the system. Its IO port is connected to the IO port of the central control unit (4), and the GND terminal of the deployment unit (1) is connected to the GND terminal of the central control unit (4).
4. The remote control system for a dynamic parallel weeding robot according to claim 2, characterized in that: The external environment acquisition module (2) is also equipped with a data processing unit (211), a data collection unit (212), and a data integration unit (213).
5. The remote control system for a dynamic parallel weeding robot according to claim 4, characterized in that: The voltage acquisition unit (201), temperature and humidity sensor (202), smoke sensor (203), light sensor (204), water immersion sensor (205), power detection unit (206), GPS positioning unit (207), surge protector unit (208), fault detection unit (209) and speed detection unit (210) input the collected data to the data processing unit (211). The data processed by the data processing unit (211) passes through the data collection unit (212) and the data integration unit (213) in sequence and is then output to the LoRa communication unit (3).
6. The remote control system for a dynamic parallel weeding robot according to claim 5, characterized in that: The Lora communication unit (3) uses the Lora node to upload its real-time data to the Lora master node, and uploads the data collected by the Lora master node to the cloud platform through WiFi communication, and uses the cloud platform to realize the control and monitoring of the weeding robot.