Path planning of mobile robot based on multi-sensor information fusion

Xu, Ruixia

doi:10.1186/s13638-019-1352-1

Cited by 16 publications

(5 citation statements)

References 9 publications

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“…The Google-based voice entity present in the robotic system is used to interact with the patient about the health parameters measured and other general information. Experimental results clearly demonstrated the usage of the proposed system in comparison to other related approaches, such as the methods suggested by Deepu et al [7], Huh and Seo [14], Chinmayi et al [6], Alli et al [1], Xu [42], Ran et al [35], and Lee et al [24]. The proposed system aims to give a supporting hand to healthcare professionals during the emergency situations such as the current pandemic virus spread.…”

Section: Discussionmentioning

confidence: 73%

“…Table 6 demonstrates the correlation of the ultrasonic sensor and image sensor with the parameters of MAPE, RMSE and Correlation. Figure 23 demonstrates the comparative analysis with the existing methods (Deepu et al [7]; Huh and Seo [14]; Chinmayi et al [6]; Alli et al [1]; Xu [42]; Ran et al [35]; Lee et al [24]) and the proposed work. It has been found that the proposed method achieves high accuracy in detecting and avoiding obstacles than the other methods.…”

Section: Resultsmentioning

confidence: 99%

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Fuzzy Guided Autonomous Nursing Robot through Wireless Beacon Network

Narayanan¹,

Krishnan

Sơn

et al. 2021

Multimed Tools Appl

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Robotics is one of the most emerging technologies today, and are used in a variety of applications, ranging from complex rocket technology to monitoring of crops in agriculture. Robots can be exceptionally useful in a smart hospital environment provided that they are equipped with improved vision capabilities for detection and avoidance of obstacles present in their path, thus allowing robots to perform their tasks without any disturbance. In the particular case of Autonomous Nursing Robots, major essential issues are effective robot path planning for the delivery of medicines to patients, measuring the patient body parameters through sensors, interacting with and informing the patient, by means of voicebased modules, about the doctors visiting schedule, his/her body parameter details, etc. This paper presents an approach of a complete Autonomous Nursing Robot which supports all the aforementioned tasks. In this paper, we present a new Autonomous Nursing Robot system capable of operating in a smart hospital environment area. The objective of the system is to identify the patient room, perform robot path planning for the delivery of medicines to a patient, and measure the patient body parameters, through a wireless BLE (Bluetooth Low Energy) beacon receiver and the BLE beacon transmitter at the respective patient rooms. Assuming that a wireless beacon is kept at the patient room, the robot follows the beacon's signal, identifies the respective room and delivers the needed medicine to the patient. A new fuzzy controller system which consists of three ultrasonic sensors and one camera is developed to detect the optimal robot path and to avoid the robot collision with stable and moving obstacles. The fuzzy controller effectively detects obstacles in the robot's vicinity and makes proper decisions for avoiding them. The navigation of the robot is implemented on a BLE tag module by using the AOA (Angle of Arrival) method. The robot uses sensors to measure the patient body parameters and updates these data to the hospital patient database system in a private cloud mode. It also makes uses of a Google assistant to interact with the patients. The robotic system was implemented on the Raspberry Pi using Matlab 2018b. The system performance was evaluated on a PC with an Intel Core i5 processor, while the solar power was used to power the system. Several sensors, namely HC-SR04 ultrasonic sensor, Logitech HD 720p image sensor, a temperature sensor and a heart rate sensor are used together with a camera to generate datasets for testing the proposed system. In particular, the system was tested on operations taking place in the context of a private hospital in Tirunelveli, Tamilnadu, India. A detailed comparison is performed, through some performance metrics, such as Correlation, Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), against the related works of Deepu et al., Huh and Seo, Chinmayi et al., Alli et al., Xu, Ran et al., and Lee et al. The experimental system validation showed that the fuzzy co...

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Section: Discussionmentioning

confidence: 73%

Section: Resultsmentioning

confidence: 99%

Fuzzy Guided Autonomous Nursing Robot through Wireless Beacon Network

Narayanan¹,

Krishnan

Sơn

et al. 2021

Multimed Tools Appl

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“…Real time position correction algorithm is a helpful method to the local and global path planning in the known environment for the path planning of the mobile robots. For this reason, it is very important to study the multi-sensor fusion technology for location the mobile robot accurately (Xu, 2019). The objective of this study is to develop an angular correction algorithm using sensor fusion of GPS and digital compass for the movement of the agricultural mobile robots in a straight line.…”

Section: Introductionmentioning

confidence: 99%

Development of angular correction algorithm for movement of agricultural mobile robots in a straight line

Unal,

Kabas,

Eceoglu

2023

CEAI

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This paper proposes the angular correction algorithm for the autonomous navigation of the agricultural mobile robots, which are driven in a straight line, with simple hardware based on the data of the digital compass and the GPS receiver. The motion of the mobile robot was accomplished by the differential drive mechanism with four driving wheels in which the overall velocity is split between left and right wheels. The two-channel DC motor controller was used to drive motors. The digital compass was used to calculate the position angle of the mobile robot with respect to the target point. A Kalman filter was used to fuse the information from GPS and digital compass. In the proposed algorithm, the mobile robot is driven in a straight line along a predefined path by calculating in real time the deviation angle difference with respect to the target point. When the robot encounters an unexpected external force varying the desired path, it achieves a smooth and stabilized straight line movement by correcting the deviation angle difference. The performance of the mobile robot was evaluated based on a total of 18 straight lines in a farmland. Standard errors of cross track error (XTE) values of straight lines for each target point were analyzed. The mean of arithmetic means was found to be 4.14 cm. The mean of Rsquare was 0.990. This value shows that the proposed angular correction algorithm is useful in driving the mobile robot in a straight line.

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“…Path planning is finding the shortest possible path between two points [3]. There exist many mature algorithms for path planning, such as Breadth First Search (BFS) and Depth First Search (DFS), and further optimization algorithms include the Dijkstra algorithm [4], A* algorithm [5], Bellman-Ford algorithm [6], etc., which traverse the map structure based on the path weight and iteratively calculate the path cost during the search, followed by backtracking to obtain an optimal solution when the calculation is completed.…”

Section: Introductionmentioning

confidence: 99%

A Reconfigurable Modular Vehicle Control Strategy Based on an Improved Artificial Potential Field

Zhou

Wang

et al. 2022

Electronics

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The reconfigurable modular vehicle group can transform into different configurations according to different requirements to be competent for various tasks and scenarios and to facilitate the utilization of robots in unstructured scenarios. Efficient and effective reconfiguration strategies and path planning are essential for improving the performance of modular vehicle groups. First, a multi-sensing four-wheel-drive Mecanum vehicle was built, which was equipped with UWB positioning (based on wireless carrier communication technology), communication based on ESP8266 modules, ultrasonic ranging and a magnetic structure. Second, concerning the indoor storage environment, a UWB two-way bilateral ranging and positioning system was designed, and the experimental accuracy for positioning could reach ±0.1 m. Third, a path planning strategy based on the improved artificial potential field method was adopted. According to the target configuration as well as the obstacle avoidance requirements, the motion space was converted into a gravitational field and a repulsive force field, and the vector superposition of the gradients was used for the path planning of each vehicle in turn. Depending on the reconfiguration command and the connection matrix, the magnetic structure would strengthen or disconnect the vehicle group configuration. Finally, the vehicle reconfiguration from the stochastic dispersion state to the target configuration and the transition between different configurations were accomplished using the proposed strategy in both simulations and experiments.

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Path planning of mobile robot based on multi-sensor information fusion

Cited by 16 publications

References 9 publications

Fuzzy Guided Autonomous Nursing Robot through Wireless Beacon Network

Fuzzy Guided Autonomous Nursing Robot through Wireless Beacon Network

Development of angular correction algorithm for movement of agricultural mobile robots in a straight line

A Reconfigurable Modular Vehicle Control Strategy Based on an Improved Artificial Potential Field

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