A sound-based positioning system with centimeter accuracy for mobile robots in a greenhouse using frequency shift compensation

Huang, Zonghao; Shiigi, Tomoo; Tsay, Lok Wai Jacky; Nakanishi, Hiroaki; Suzuki, Tetsuhito; Ogawa, Yuichi; Kondo, Naoshi

doi:10.1016/j.compag.2021.106235

Cited by 16 publications

(11 citation statements)

References 25 publications

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“…Over the years, various localization and navigation methods on mobile platforms have been developed for different usage environments, from field weeding robots (McCool et al, 2018) to transportation robots (Ye et al, 2017), from LIDAR detection and navigation approaches (Grimstad et al, 2018), to probabilistic localization techniques (Xu et al, 2021), and to the use of topological maps (Fentanes et al, 2015). The Doppler displacement compensation algorithm based on the carrier frequency detection realized localization and navigation of the small mobile platform in greenhouse environments (Huang et al, 2021). The navigation control of the robot mobile platform based on encoder‐based velocity estimates and 2D LIDAR scans was carried out on a polytunnel farm (Xiong et al, 2019).…”

Section: Related Workmentioning

confidence: 99%

Development, integration, and field evaluation of an autonomous citrus‐harvesting robot

Yin

Sun

Ren

et al. 2023

Journal of Field Robotics

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Citrus harvesting is a labor-intensive and time-intensive task. As the global population continues to age, labor costs are increasing dramatically. Therefore, the citrus-harvesting robot has attracted considerable attention from the business and academic communities. However, robotic harvesting in unstructured and natural citrus orchards remains a challenge. This study aims to address some challenges faced in commercializing citrus-harvesting robots. We present a fully integrated, autonomous, and innovative solution for citrus-harvesting robots to overcome the harvesting difficulties derived from the natural growth characteristics of citrus. This solution uses a fused simultaneous localization and mapping algorithm based on multiple sensors to perform high-precision localization and navigation for the robot in the field orchard. Besides, a novel visual method for estimating fruit poses is proposed to cope with the randomization of citrus growth orientations. Further, a new end-effector is designed to improve the success and conformity rate of citrus stem cutting. Finally, a fully autonomous harvesting robot system has been developed and integrated. Field evaluations showed that the robot could harvest citrus continuously with an overall success rate of 87.2% and an average picking time of 10.9 s/fruit. These efforts provide a solid foundation for the future commercialization of citrus-harvesting robots.

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Section: Related Workmentioning

confidence: 99%

Development, integration, and field evaluation of an autonomous citrus‐harvesting robot

Yin

Sun

Ren

et al. 2023

Journal of Field Robotics

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“…Besides the device used in the greenhouse experiment, for the dynamic experiment the wireless trigger signal which was emitted by the Zigbee device was used, the four speakers were set at (2.00±0.04) m height at four corners and the Doppler compensation algorithm [16] was also adopted in the distance calculation. Meanwhile, the motion capture system (Vicon Tracker, Vicon Industries Inc., USA ), with 0.15 mm accuracy [17] , was used with eight cameras at the edges for providing the reference position to evaluate the accuracy of SSSLPS during movement, as shown in Figure 6.…”

Section: Dynamic Experimentsmentioning

confidence: 99%

Static and dynamic evaluations of acoustic positioning system using TDMA and FDMA for robots operating in a greenhouse

Tsay

Shiigi

Zhao

et al. 2022

International Journal of Agricultural and Biological Engineering

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Acoustic positioning system has great potential to be applied in a greenhouse due to its centimeter-level accuracy, low cost, and ability of extensive greenhouse coverage. Spread Spectrum Sound-based local positioning system (SSSLPS) was proposed to be a navigation tool for multiple agricultural robots by the authors' research team. However, to increase the system capacity for positioning multiple robots in a greenhouse, the near-far problem caused by the interference between speakers needs to be overcome. The use of different access methods, Time Division Multiple Access (TDMA) or Frequency Division Multiple Access (FDMA), is essential in the SSSLPS system for solving the near-far problem. The static positioning in a greenhouse was first evaluated by setting different parameters to determine the optimal signal setting for a dynamic experiment. From that, the moving robot tests were added with a motion capture system and tested the performance of TDMA and FDMA. The results demonstrated that TDMA can be used in a stationary sound-based positioning system with 12.2 mm accuracy, but it has a time delay problem in dynamic positioning. A simulation was designed to mimic the position error increases with different moving speeds. Although FDMA has the sound damping problem in high-frequency regions creating a peak detection issue, it achieved a higher accuracy with an average position error of 62.1 mm compared to 180.3 mm of TDMA. This study shows that the TDMA method is suitable for static measurements, while the FDMA method is suitable for measuring dynamic objects and controlling mobile robots.

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“…However, the UWB-based positioning systems are susceptible to the multi-path effect and non-line-of-sight propagation. The 3.1-10.6 GHz frequency band may interfere with existing wireless systems [12]. According to the installation position of the microphone, the sound-based positioning system can be divided into active architecture and passive architecture.…”

Section: Introductionmentioning

confidence: 99%

Precise visual positioning of agricultural mobile robots with a fiducial marker reprojection approach

Zhang,

Gong,

Sun

et al. 2023

Meas. Sci. Technol.

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Semi-structured greenhouse environment often features repetitive and weak texture, naturally bringing challenges to high-precision vision-based positioning techniques. This paper proposes a precise visual positioning method for agricultural mobile robots in the greenhouse, which improves their positioning accuracy via discriminatively minimizing fiducial marker reprojection errors. First, fiducial markers are used to enhance environment features, and a markers-based visual positioning task is formulated as a Perspective-n-Point (PnP) problem. The projection constraints of keypoints and the pose constraints of the coordinate systems provide a theoretical basis for robot positioning. Second, a reprojection error minimization approach is proposed by taking into account the markers’ distance and image noise. Far-away markers are more prone to greater observation errors than those close to the robots, the improved PnP algorithm considering distance weighting ensures higher positioning accuracy. Synthetic and field experiments are carried out to evaluate the performance of the proposed method. Synthetic experiments show that the rotation error and translation error of the proposed method are less than 0.7 degrees and 0.5% within a range of 12 m. The MAE and RMSE of field dynamic positioning experiments are 8.57cm and 8.59cm, respectively. Experimental results show that the proposed method is significantly better than traditional methods in dealing with distance-related noise at keypoints.

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A sound-based positioning system with centimeter accuracy for mobile robots in a greenhouse using frequency shift compensation

Cited by 16 publications

References 25 publications

Development, integration, and field evaluation of an autonomous citrus‐harvesting robot

Development, integration, and field evaluation of an autonomous citrus‐harvesting robot

Static and dynamic evaluations of acoustic positioning system using TDMA and FDMA for robots operating in a greenhouse

Precise visual positioning of agricultural mobile robots with a fiducial marker reprojection approach

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