Accurate and Real-Time 3-D Tracking for the Following Robots by Fusing Vision and Ultrasonar Information

Wang, Mengmeng; Liu, Yong; Su, Daobilige; Liao, Yufan; Shi, Lei; Xu, Jinhong; Miró, Jaime Valls

doi:10.1109/tmech.2018.2820172

Cited by 55 publications

(22 citation statements)

References 21 publications

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“…For instance, diver-following robots sometimes plan a straight-line trajectory to remain immediately behind the diver (Islam and Sattar, 2017). A similar strategy is adopted by ground robots as well (Brookshire, 2010; Doisy et al, 2012; Wang et al, 2018a), with an additional planning component for obstacle avoidance. As illustrated in Figure 15, person-following UGVs can use tools from prospective geometry to get the relative homography of the orthogonal planes and then find the optimal path along the ground plane by keeping safe distances from the person and obstacles.…”

Section: State-of-the-art Approachesmentioning

confidence: 99%

Person-following by autonomous robots: A categorical overview

Islam

Hong

Sattar

2019

The International Journal of Robotics Research

109

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A wide range of human-robot collaborative applications in diverse domains such as manufacturing, health care, the entertainment industry, and social interactions, require an autonomous robot to follow its human companion. Different working environments and applications pose diverse challenges by adding constraints on the choice of sensors, the degree of autonomy, and dynamics of a person-following robot. Researchers have addressed these challenges in many ways and contributed to the development of a large body of literature. This paper provides a comprehensive overview of the literature by categorizing different aspects of person-following by autonomous robots. Also, the corresponding operational challenges are identified based on various design choices for ground, underwater, and aerial scenarios. In addition, state-of-the-art methods for perception, planning, control, and interaction are elaborately discussed and their applicability in varied operational scenarios are presented. Then, some of the prominent methods are qualitatively compared, corresponding practicalities are illustrated, and their feasibility is analyzed for various usecases. Furthermore, several prospective application areas are identified, and open problems are highlighted for future research.

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Section: State-of-the-art Approachesmentioning

confidence: 99%

Person-following by autonomous robots: A categorical overview

Islam

Hong

Sattar

2019

The International Journal of Robotics Research

109

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“…Xu et al [ 3 ] realized the positioning of indoor mobile robots by installing the camera above the robot head and extracting the ceiling features. Wang et al [ 4 ] constructed a three-diensional (3D) human tracking system by fusing the information of visual and ultrasonic sensors. Liu et al [ 5 ] analyzed target tracking under different illumination conditions in intelligent monitoring of public places.…”

Section: Introductionmentioning

confidence: 99%

A Method of Multiple Dynamic Objects Identification and Localization Based on Laser and RFID

Liu

Wang

et al. 2020

Sensors

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In an indoor environment, object identification and localization are paramount for human-object interaction. Visual or laser-based sensors can achieve the identification and localization of the object based on its appearance, but these approaches are computationally expensive and not robust against the environment with obstacles. Radio Frequency Identification (RFID) has a unique tag ID to identify the object, but it cannot accurately locate it. Therefore, in this paper, the data of RFID and laser range finder are fused for the better identification and localization of multiple dynamic objects in an indoor environment. The main method is to use the laser range finder to estimate the radial velocities of objects in a certain environment, and match them with the object’s radial velocities estimated by the RFID phase. The method also uses a fixed time series as “sliding time window” to find the cluster with the highest similarity of each RFID tag in each window. Moreover, the Pearson correlation coefficient (PCC) is used in the update stage of the particle filter (PF) to estimate the moving path of each cluster in order to improve the accuracy in a complex environment with obstacles. The experiments were verified by a SCITOS G5 robot. The results show that this method can achieve an matching rate of 90.18% and a localization accuracy of 0.33m in an environment with the presence of obstacles. This method effectively improves the matching rate and localization accuracy of multiple objects in indoor scenes when compared to the Bray-Curtis (BC) similarity matching-based approach as well as the particle filter-based approach.

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“…Kalman filtering is one of the most significant method. In Wang et al (2018), a real-time robotic 3-D human tracking system is proposed for a monocular camera with an ultrasonic sensor by an extended Kalman filter, and multisensor fusion algorithm is applied to this system. In Wang et al (2018), a multimodal data fusion method is applied to integrate these outcomes so that vehicle-tracking tasks can be achieved.…”

Section: Introductionmentioning

confidence: 99%

“…In Wang et al (2018), a real-time robotic 3-D human tracking system is proposed for a monocular camera with an ultrasonic sensor by an extended Kalman filter, and multisensor fusion algorithm is applied to this system. In Wang et al (2018), a multimodal data fusion method is applied to integrate these outcomes so that vehicle-tracking tasks can be achieved. The linear prediction coding technique of Ding et al (2019) is combined with the data fusion process to predict the target initial state for higher positioning accuracy, where the proposed algorithm can improve the target positioning accuracy and help to identify stationary and tangentially moving targets.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional target tracking strategy based on guidance laws and optimal information fusion

Dong

Feng

Tai

2020

Transactions of the Institute of Measurement and Control

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This paper presents a method for pursuer to track a moving target in a three-dimensional space. The method is based on the guidance laws combined with the kinematics equations of the pursuer and the target. The maneuvers of the target are prior unknown to the pursuer. Guidance laws used for tracking are the deviated pursuit and the proportional navigation, and the method presents a family of navigation laws resulting in a rich behavior for different parameters. For the three-dimensional scenario, two cases-not presenting interference and presenting interference are considered. In the absence of interference, the control strategy is proposed to implement the problem of tracking. In the presence of interference, an optimal information fusion Kalman filter weighted by scalars and guidance laws are combined to improve the trajectory tracking precision, and the combination can enrich the application range of information fusion and guidance laws. Simulations are conducted to demonstrate the effectiveness and reliability of the proposed control strategy.

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Accurate and Real-Time 3-D Tracking for the Following Robots by Fusing Vision and Ultrasonar Information

Cited by 55 publications

References 21 publications

Person-following by autonomous robots: A categorical overview

Person-following by autonomous robots: A categorical overview

A Method of Multiple Dynamic Objects Identification and Localization Based on Laser and RFID

Three-dimensional target tracking strategy based on guidance laws and optimal information fusion

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