Intelligent walking-replacing robot control system and control method thereof

Abstract

The invention is suitable for the technical field of intelligent scooters, and provides an intelligent scooter robot control system and a control method thereof.The intelligent scooter robot control system comprises a health detection module, a toppling detection module and a collision early warning module, and the health detection module is used for presetting a health data set, collecting real-time physical sign data of a user in a vehicle and sending the real-time physical sign data to the toppling detection module; the health state of a user is matched according to a preset health data set, processing is carried out according to a detection result, the toppling detection module is used for detecting the inclination angle of a vehicle in real time, judging the posture state of the vehicle according to the inclination angle and carrying out processing according to the posture state, and the collision early warning module is used for monitoring the distance of an obstacle in front of the vehicle in real time. The preset collision early-warning level is matched according to the distance between the obstacles in front of the vehicle, collision early-warning work is conducted according to the collision early-warning level, comprehensive and reliable safety guarantee is provided for a user by arranging the health detection module, the toppling detection module and the collision early-warning module, and the travel safety and personal safety of the user are improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent mobility scooter technology, and more specifically, to an intelligent mobility robot control system and its control method. Background Technology

[0002] With the increasing aging of society, the demand for personal mobility assistive devices is growing. Traditional four-wheeled mobility vehicles, as a widely used short-distance mobility solution, provide basic mobility for the elderly with limited mobility and those recovering from injuries.

[0003] However, traditional four-wheeled mobility vehicles only solve basic mobility needs and have significant shortcomings in terms of driving safety and health care. Traditional four-wheeled mobility vehicles do not have the ability to detect users' vital signs data and cannot provide timely feedback when users have abnormal physical conditions while traveling. Traditional four-wheeled mobility vehicles also do not have active safety protection capabilities and cannot proactively anticipate risks for users during driving and provide timely warnings to remind users to avoid risks. Summary of the Invention

[0004] To address the shortcomings of existing technologies, the present invention aims to provide an intelligent personal mobility robot control system and its control method.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an intelligent personal mobility robot control system, comprising a health detection module, a tipping detection module, and a collision warning module, wherein the health detection module is used to preset a health dataset, collect real-time vital sign data of users inside the vehicle, match the user's health status according to the preset health dataset, and process the detection results; The tilt detection module is used to detect the tilt angle of the vehicle in real time, determine the vehicle's attitude state based on the tilt angle, and process the attitude state accordingly. The collision warning module is used to monitor the distance to obstacles in front of the vehicle in real time, match the preset collision warning level according to the distance to obstacles in front of the vehicle, and perform collision warning work according to the collision warning level.

[0006] The present invention is further configured such that: the health detection module includes a health status preset unit, a vital sign data acquisition unit, a health status analysis unit, and a detection result processing unit; wherein, The health status preset unit is used to preset a health dataset based on the user's physical condition; The vital signs data acquisition unit is used to collect vital signs data of users inside the vehicle; The health status analysis unit is used to match the collected vital sign data with a preset health status dataset to obtain the user's health status. The test result processing unit is used to process health test results based on health status.

[0007] The present invention is further configured such that: the tilt detection module includes an attitude data acquisition unit, a vehicle attitude judgment unit, and a judgment result processing unit; wherein, The attitude data acquisition unit is used to detect the vehicle's tilt angle in real time and obtain the vehicle's tilt angle information; The vehicle attitude determination unit is used to determine the vehicle's attitude state based on the collected tilt angle data. The judgment result processing unit is used to process the vehicle's attitude state.

[0008] The present invention is further configured such that: the collision warning module includes a distance monitoring unit, a collision warning analysis unit, and a warning result processing unit; wherein, The distance monitoring unit is used to collect the distance between the vehicle and obstacles in front of it; The collision warning analysis unit is used to match a preset collision warning level based on the distance between the vehicle and the obstacle in front; The early warning result processing unit is used to perform collision warning work according to the collision warning level.

[0009] The invention is further configured such that: a pressure sensor is provided under the driver's seat of the vehicle, which is used to identify whether there is a person in the vehicle to trigger a health detection; a tilt sensor is provided in the middle of the chassis of the vehicle, which is used to measure the tilt angle of the vehicle; a distance sensor is provided at the front of the vehicle, which is used to collect the distance between the vehicle and obstacles in front; and an emergency communication module is also integrated in the vehicle, which is used to send emergency help information to preset emergency contacts.

[0010] A method for controlling an intelligent personal mobility robot, using an intelligent personal mobility robot control system as described above, includes the following steps: Step S1: Establish a health dataset based on the user's physical condition; Step S2: Collect multi-source data in real time, including user vital signs data, vehicle tilt angle data, and distance data between the vehicle and obstacles in front; Step S3: Analyze and process the collected data from multiple sources to obtain multi-source detection results, including health detection results, tipping judgment results, and collision warning results; Step S4: Perform corresponding processing based on the results of multiple tests, including processing of health test results, processing of tipping judgment results, and processing of collision warning results.

[0011] The present invention is further configured to: establish a health dataset including: A pre-set health dataset is established. Based on the user's physical condition, the health status corresponding to different vital signs data of the user is determined, and the pre-set vital sign data of the user in a normal state is obtained. The user's personalized physical condition pre-set health dataset is used to judge the user's health status. The physical differences of the elderly population are large. By creating such a personalized dataset, the health status of users can be judged more accurately.

[0012] The present invention is further configured such that step S2 further includes: Step S21: Detecting a person inside the vehicle triggers a health check and collects real-time vital signs data of the user inside the vehicle; Step S22: Real-time acquisition of the vehicle's first tilt angle Q1 and second tilt angle Q2. The first tilt angle Q1 is the vehicle's side tilt angle, and the second tilt angle Q2 is the vehicle's pitch tilt angle. By simultaneously acquiring the vehicle's side tilt angle and pitch tilt angle, the vehicle's attitude state can be comprehensively determined, improving the accuracy of detection. Step S23: Detect the vehicle's operating status. When the vehicle is in a forward-moving state, activate the distance sensor to collect the distance L between the vehicle and the obstacle in front in real time.

[0013] The present invention is further configured such that step S3 includes: Step S31: Match the collected real-time vital signs data with a preset health dataset. Compare the real-time vital signs data with the preset vital signs data. When the real-time vital signs data is within the range of the preset vital signs data, determine that the user's vital signs data is normal. When the real-time vital signs data is not within the range of the preset vital signs data, determine that the user's vital signs data is abnormal. Step S32: Match the tilt threshold q1 of the first tilt angle Q1 and the tilt threshold q2 of the second tilt angle Q2 of the vehicle, continuously judge the vehicle's attitude state within N seconds, and judge the vehicle tilting when either tilt angle Q1 or Q2 is greater than its corresponding tilt threshold M times, and record the vehicle tilting time T. By continuously judging M times within the triggering N seconds, and triggering the corresponding operation only when all conditions are met, the false alarm rate can be effectively controlled. Step S33: Match the collision warning level S based on the distance L between the vehicle and the obstacle ahead. ; In this system, A, B, C, and D represent four collision warning levels corresponding to the distance L between the vehicle and the obstacle ahead. A indicates no collision risk, B indicates Level 1 collision risk, C indicates Level 2 collision risk, and D indicates Level 3 collision risk. These represent three threshold values ​​corresponding to the distance L between the vehicle and the obstacle in front. Indicates the first threshold. This represents the second threshold. This represents the third threshold.

[0014] The present invention is further configured such that step S4 includes: Step S41: When the health status is normal, no health test result processing is performed. When the health status is abnormal, health test result processing is performed, and a request for help for abnormal vital signs is sent to the preset emergency contact. The request for help for abnormal vital signs includes real-time location, real-time time and abnormal vital signs data. Step S42: When the vehicle tipps over, cut off the motor power output. When the vehicle tipping duration T is greater than the preset vehicle tipping duration threshold t, send a tipping assistance message to the preset emergency contact. The tipping assistance message includes the real-time location, real-time time, and tipping prompt. By setting the vehicle tipping duration threshold t, sufficient time is given for the users in the vehicle to save themselves. If the vehicle tipping continues for more than t seconds, it is determined that there is no effective self-rescue action, and it is necessary to send a tipping assistance message to the emergency contact. Step S43: Perform collision warning according to the collision warning level S, where A corresponds to no collision warning, B corresponds to the first collision warning, C corresponds to the second collision warning, and D corresponds to the third collision warning.

[0015] By adopting the above technical solution, this application includes at least one of the following beneficial technical effects: This invention features a health monitoring module that monitors the vital signs of users inside the vehicle in real time. It also pre-sets a health dataset based on each user's individual physical condition to assess their health status. Given the significant differences in health among the elderly, this personalized dataset allows for a more accurate assessment of their health. Furthermore, a tilt detection module monitors the vehicle's posture in real time, automatically cutting off power output when the vehicle tilts and determining the user's self-rescue capabilities. If the user is unable to quickly rescue themselves, a distress message is sent to a pre-set emergency contact, ensuring the user's safety. Finally, a collision warning module detects the distance to obstacles in front of the vehicle in real time and issues warnings based on the distance, reminding the user to avoid collision risks and improving driving safety. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the system module composition in this invention; Figure 2 This is a schematic diagram of the overall control method in this invention; Figure 3 This is a flowchart illustrating the health detection process in this invention; Figure 4 This is a flowchart illustrating the collision warning process in this invention. Detailed Implementation

[0017] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0018] It should be noted that, unless otherwise specified, all technical and scientific terms used in this application have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0019] Please see Figure 1-4 The present invention provides the following technical solutions: Example 1, please refer to Figure 1 A smart mobility robot control system includes a health detection module, a tipping detection module, and a collision warning module. The health detection module is used to preset a health dataset, collect real-time vital sign data of users inside the vehicle, match the user's health status according to the preset health dataset, and process the detection results. The tilt detection module is used to detect the tilt angle of the vehicle in real time, determine the vehicle's attitude state based on the tilt angle, and process the attitude state accordingly. The collision warning module is used to monitor the distance to obstacles in front of the vehicle in real time, match the preset collision warning level according to the distance to obstacles in front of the vehicle, and perform collision warning work according to the collision warning level.

[0020] The health monitoring module includes a health status preset unit, a vital sign data acquisition unit, a health status analysis unit, and a test result processing unit; among which, The health status preset unit is used to preset a health dataset based on the user's physical condition; The vital signs data acquisition unit is used to collect vital signs data of users inside the vehicle; The health status analysis unit is used to match the user's vital signs data with a preset health status dataset to obtain the user's health status. The test result processing unit is used to process health test results based on health status.

[0021] The tipping detection module includes an attitude data acquisition unit, a vehicle attitude judgment unit, and a judgment result processing unit; among which, The attitude data acquisition unit is used to detect the vehicle's tilt angle in real time and obtain the vehicle's tilt angle information; The vehicle attitude determination unit is used to determine the vehicle's attitude state based on the collected tilt angle data. The judgment result processing unit is used to process the vehicle's attitude state.

[0022] The collision warning module includes a distance monitoring unit, a collision warning analysis unit, and a warning result processing unit; among which, The distance monitoring unit is used to collect the distance between the vehicle and obstacles in front of it; The collision warning analysis unit is used to match a preset collision warning level based on the distance between the vehicle and the obstacle in front; The early warning result processing unit is used to perform collision warning work according to the collision warning level.

[0023] Furthermore, a pressure sensor is installed under the driver's seat to detect whether there is someone inside the vehicle. Once someone is detected, a health check is triggered. A tilt sensor is installed in the middle of the chassis. The tilt sensor can be a dual-axis tilt sensor to measure both roll and pitch. An ultrasonic sensor is installed in the middle of the front bumper to monitor the distance to obstacles in front of the vehicle. Ultrasonic sensors are low-cost, suitable for all weather conditions, cost-effective, and reliable. An emergency communication module is also integrated into the vehicle to send emergency help messages to preset emergency contacts.

[0024] Example 2, please refer to Figure 2 A control method for an intelligent personal mobility robot, used to implement an intelligent personal mobility robot control system, includes the following steps: Step S1: Establish a health dataset based on the user's physical condition; Step S2: Collect multi-source data in real time, including user vital signs data, vehicle tilt angle data, and distance data between the vehicle and obstacles in front; Step S3: Analyze and process the collected data from multiple sources to obtain multi-source detection results, including health detection results, tipping judgment results, and collision warning results; Step S4: Perform corresponding processing based on the results of multiple tests, including processing of health test results, processing of tipping judgment results, and processing of collision warning results.

[0025] Furthermore, when establishing a health dataset, specifically: Establish a preset health dataset. Based on the user's physical condition, determine the corresponding health status for different vital signs. For example, the vital signs data include heart rate, blood oxygen saturation, microcirculation, systolic blood pressure, and diastolic blood pressure. The preset normal range for the user's vital signs data is: {Heart rate: 60~100 beats / min; Blood oxygen saturation: 95%~100%; Microcirculation: above 0.5%; Systolic blood pressure: 90~140 mmHg; Diastolic blood pressure: 60~90 mmHg.} Vital signs data outside the above ranges are considered abnormal.

[0026] Step S2 further includes: Step S21: The pressure sensor under the driver's seat detects someone in the vehicle, triggering a health check and collecting real-time vital signs data of the user, including five real-time vital signs: heart rate, blood oxygen, microcirculation, systolic blood pressure, and diastolic blood pressure. For example, the user's real-time vital signs data are: {Heart rate: 78 beats / min; Blood oxygen: 87.2%; Microcirculation: 0.5%; Systolic blood pressure: 128 mmHg; Diastolic blood pressure: 82 mmHg.} Step S22: The tilt sensor of the vehicle chassis collects the first tilt angle Q1 and the second tilt angle Q2 of the vehicle in real time. The first tilt angle Q1 is the side tilt angle of the vehicle, and the second tilt angle Q2 is the pitch tilt angle of the vehicle. Step S23: Detect the vehicle's operating status. When the vehicle is in a forward-moving state, activate the ultrasonic sensor to collect the distance L between the vehicle and the obstacle in front in real time.

[0027] Further, see Figure 3 When analyzing the collected user vital sign data, the specific steps are as follows: Step S31: Match the collected vital sign data with a preset health dataset to obtain the user's health status, including abnormal and normal vital sign data. For example, based on the user's real-time vital sign data: {heart rate: 78 bpm; blood oxygen: 87.2%; microcirculation: 0.5%; systolic blood pressure: 128 mmHg; diastolic blood pressure: 82 mmHg}, match it with the user's preset normal range of vital sign data: {heart rate: 60~100 bpm; blood oxygen: 95%~100%; microcirculation: above 0.5%; systolic blood pressure: 90~140 mmHg; diastolic blood pressure: 60~90 mmHg}. The user's real-time blood oxygen data is found to be abnormal, thus the user's vital sign data is judged to be abnormal. Furthermore, the analysis of the collected vehicle tilt angle data specifically involves: Step S32: Match the tilt threshold q1 and the tilt threshold q2 of the vehicle's first tilt angle and second tilt angle according to the first tilt angle Q1 and the second tilt angle Q2. Ideally, the first tilt angle and the second tilt angle of the vehicle are both 0°. In reality, there may be an error of 5° to 10°. During normal driving, the first tilt angle of the vehicle will not exceed 45°. Here, q1 is set to 60° as the threshold for judging the side tilt of the vehicle. During normal driving, the second tilt angle of the vehicle will deviate due to uphill and downhill slopes. Usually, the maximum slope angle that the vehicle can safely drive is between 15° and 20°. Here, q2 is set to 45° as the threshold for judging the pitch tilt of the vehicle. The vehicle's attitude state is continuously judged within N seconds. When either tilt angle Q1 or Q2 exceeds its corresponding tilt threshold M times, the vehicle is judged to have tilted and the tilting time T is recorded. N is set to 2 seconds and M to 5 times. By making 5 consecutive judgments within the 2-second trigger time and triggering the corresponding operation only when all conditions are met, the false alarm rate can be effectively controlled.

[0028] Further, see Figure 4 When analyzing the collected distance data between the vehicle and obstacles in front, the specific steps are as follows: Step S33: Match the collision warning level S based on the distance L between the vehicle and the obstacle ahead. ; In this system, A, B, C, and D represent four collision warning levels corresponding to the distance L between the vehicle and the obstacle ahead. A indicates no collision risk, B indicates Level 1 collision risk, C indicates Level 2 collision risk, and D indicates Level 3 collision risk. These represent three threshold values ​​corresponding to the distance L between the vehicle and the obstacle in front. Indicates the first threshold. This represents the second threshold. This represents the third threshold. Referring to engineering and human factors engineering principles in the design of reversing radar systems, these are empirical values ​​set by engineers based on a comprehensive trade-off between safety and human-machine interaction. Set to 50cm. Set to 25cm. Set to 10cm.

[0029] Furthermore, the processing of health test results is specifically as follows: Step S41: When the health status is normal, no health test result processing is performed. When the health status is abnormal, health test result processing is performed. For example, when the vital signs data is abnormal, a vital signs data abnormality request information is sent to the preset emergency contact. The vital signs abnormality request information includes real-time location, real-time time, and abnormal vital signs data.

[0030] Furthermore, the specific steps for processing the dumping judgment results are as follows: Step S42: When the vehicle tipps over, cut off the motor power output. When the vehicle tipping duration T is greater than the preset vehicle tipping duration threshold t, send a tipping assistance message to the preset emergency contact. The tipping assistance message includes the real-time location, real-time time, and tipping prompt. The vehicle tipping duration threshold t can be set to 10 seconds to give the user inside the vehicle enough time to save themselves. If the vehicle tipping continues for more than 10 seconds, it is determined that there is no effective self-rescue action, and a tipping assistance message needs to be sent to the emergency contact.

[0031] Furthermore, the specific steps for processing collision warning results are as follows: Step S43: Perform collision warning according to the collision warning level S, where A corresponds to no collision warning, i.e. the buzzer is off; B corresponds to the first collision warning, i.e. the buzzer sounds slowly; C corresponds to the second collision warning, i.e. the buzzer sounds quickly; and D corresponds to the third collision warning, i.e. the buzzer sounds constantly.

[0032] Obviously, the embodiments described above are merely some, not all, embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention.

Claims

1. An intelligent walking robot control system, characterized in that: The system comprises a health detection module, a dumping detection module and a collision warning module. The health detection module is configured to preset a health data set, collect real-time physical data of a user in the vehicle, match the health status of the user according to the preset health data set, and process according to the detection result. The dumping detection module is configured to detect the inclination angle of the vehicle in real time, determine the attitude state of the vehicle according to the inclination angle, and process according to the attitude state. The collision warning module is configured to monitor the distance of the obstacle in front of the vehicle in real time, match the preset collision warning level according to the distance of the obstacle in front of the vehicle, and perform collision warning work according to the collision warning level. 2.The intelligent walking robot control system according to claim 1, characterized in that: The health detection module comprises a health state preset unit, a physical data collection unit, a health state analysis unit and a detection result processing unit. The health state preset unit is configured to preset a health data set based on the physical condition of the user. The physical data collection unit is configured to collect physical data of a user in the vehicle. The health state analysis unit is configured to match the preset health status data set according to the physical data, and obtain the health status of the user. The detection result processing unit is configured to process the health detection result according to the health status. 3.The intelligent walking robot control system according to claim 2, characterized in that: The dumping detection module comprises an attitude data collection unit, a vehicle attitude determination unit and a determination result processing unit. The attitude data collection unit is configured to detect the inclination angle of the vehicle in real time, and obtain the inclination angle of the vehicle. The vehicle attitude determination unit is configured to determine the attitude state of the vehicle according to the collected inclination angle. The determination result processing unit is configured to process according to the attitude state of the vehicle.

4. The intelligent mobility robot control system according to claim 3, wherein: The collision warning module comprises a distance monitoring unit, a collision warning analysis unit and a warning result processing unit. The distance monitoring unit is configured to collect the distance between the vehicle and the obstacle in front of the vehicle. The collision warning analysis unit is configured to match the preset collision warning level according to the distance of the obstacle in front of the vehicle. The warning result processing unit is configured to perform collision warning work according to the collision warning level.

5. The intelligent mobility robot control system according to claim 4, wherein: The pressure sensor is arranged below the driver's seat of the vehicle, the inclination sensor is arranged in the middle of the chassis of the vehicle, the distance measuring sensor is arranged at the front of the vehicle, and the emergency communication module is integrated in the vehicle.

6. A control method of the intelligent walking robot, using the intelligent walking robot control system according to any one of claims 1-5, characterized in that, The method comprises the following steps: Step S1: establishing a health data set based on the physical condition of the user; Step S2: collecting real-time multi-party data, including physical data of the user, inclination data of the vehicle and distance data between the vehicle and the obstacle in front of the vehicle; Step S3: analyzing and processing the collected multi-party data to obtain multi-party detection results, including health detection results, dumping determination results and collision warning results; Step S4: processing corresponding work according to the multi-party detection results, including health detection result processing, dumping determination result processing and collision warning result processing. 7.The intelligent walking robot control method according to claim 6, characterized in that: The establishment of the health data set comprises: Presetting a health data set, determining the health status corresponding to different physical data of the user based on the physical condition of the user, and obtaining the preset physical data of the user in the normal state. 8.The intelligent walking robot control method according to claim 7, characterized in that: The step S2 further comprises: Step S21: recognizing that there is a person in the vehicle, triggering health detection, and collecting real-time physical data of the user in the vehicle; Step S22: Real-time collection of the first direction angle Q1 and the second direction angle Q2, the first direction angle Q1 being the side inclination angle of the vehicle, and the second direction angle Q2 being the pitch inclination angle of the vehicle; Step S23: Detection of the running state of the vehicle, and starting the distance measuring sensor when the running state of the vehicle is the forward state, and real-time collection of the distance L between the vehicle and the front obstacle. 9.The intelligent walking robot control method according to claim 8, characterized in that: The step S3 comprises: Step S31: Matching the collected real-time physical data with the preset health data set, comparing the real-time physical data with the preset physical data, judging that the physical data of the user is normal when the real-time physical data is within the range of the preset physical data, and judging that the physical data of the user is abnormal when the real-time physical data is not within the range of the preset physical data; Step S32: Matching the first direction angle Q1 and the second direction angle Q2 with the first direction angle dumping threshold q1 and the second direction angle dumping threshold q2 of the vehicle, and continuously judging the attitude state of the vehicle within N seconds, and judging that the vehicle is dumping when any one of Q1 and Q2 is greater than the corresponding dumping threshold M times, and recording the dumping duration T of the vehicle; Step S33: Matching the distance L between the vehicle and the front obstacle with the collision warning level S, ； wherein A, B, C, D represent four kinds of collision warning levels corresponding to the distance L of the vehicle and the front obstacle respectively, A represents no collision risk, B represents first-class collision risk, C represents second-class collision risk, and D represents third-class collision risk, respectively represent three kinds of threshold values corresponding to the distance L of the vehicle and the front obstacle, represents the first threshold value, represents the second threshold value, represents the third threshold value. 10.The intelligent walking robot control method according to claim 9, characterized in that: The step S4 comprises: Step S41: When the health state is the normal physical data, no health detection result processing is performed, and when the health state is the abnormal physical data, health detection result processing is performed, and the abnormal physical data help information is sent to the preset emergency contact, the abnormal physical data help information comprising the real-time position, the real-time time and the abnormal physical data; Step S42: When the vehicle is dumping, the motor power output is cut off, and when the dumping duration T of the vehicle is greater than the preset vehicle dumping duration threshold t, the dumping help information is sent to the preset emergency contact, the dumping help information comprising the real-time position, the real-time time and the dumping prompt; Step S43: Collision warning work according to the collision warning level S, wherein A corresponds to no collision warning work, B corresponds to the first collision warning work, C corresponds to the second collision warning work, and D corresponds to the third collision warning work.

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