Person Following Robot Using Selected Online Ada-Boosting with Stereo Camera

Chen, Bao Xin; Sahdev, Raghavender; Tsotsos, John K.

doi:10.1109/crv.2017.55

Cited by 42 publications

(26 citation statements)

References 27 publications

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“…However, since infrared sensors perform poorly in the presence of sunlight, they are not good choices for outdoor environments. The use of stereo cameras can get rid of this problem, as depth information can be approximated by using triangulation techniques (Chen et al, 2017b; Satake et al, 2013). Laser range finders (LRFs) are also widely used by person-following UGVs (Chung et al, 2012; Susperregi et al, 2013).…”

Section: Categorization Of Autonomous Person-following Behaviorsmentioning

confidence: 99%

Person-following by autonomous robots: A categorical overview

Islam

Hong

Sattar

2019

The International Journal of Robotics Research

111

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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: Categorization Of Autonomous Person-following Behaviorsmentioning

confidence: 99%

Person-following by autonomous robots: A categorical overview

Islam

Hong

Sattar

2019

The International Journal of Robotics Research

111

View full text Add to dashboard Cite

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“…The two main categories of visual sensors able to catch depth information are stereo and RGB-D cameras. Several works [15][16][17][18][19][20] use the first approach to approximate the distance information by triangulation methods applied on two or more RGB views of the same scene. However, the most used visual sensors for person detection are RGB-D cameras [21][22][23][24][25][26][27][28][29][30][31][32] that are able to get both RGB images and depth maps by exploiting infrared light.…”

Section: Person Followingmentioning

confidence: 99%

“…More recently, machine learning techniques have been used to solve the person-following task. Chen et al [19] used an online AdaBoost classifier initialized on a manually-selected bounding box of the target person. Chen [31], instead, used an upper-body detector based on an SVM to get the human position and extract relevant features used during the tracking phase.…”

Section: Person Followingmentioning

confidence: 99%

A Cost-Effective Person-Following System for Assistive Unmanned Vehicles with Deep Learning at the Edge

et al. 2020

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The vital statistics of the last century highlight a sharp increment of the average age of the world population with a consequent growth of the number of older people. Service robotics applications have the potentiality to provide systems and tools to support the autonomous and self-sufficient older adults in their houses in everyday life, thereby avoiding the task of monitoring them with third parties. In this context, we propose a cost-effective modular solution to detect and follow a person in an indoor, domestic environment. We exploited the latest advancements in deep learning optimization techniques, and we compared different neural network accelerators to provide a robust and flexible person-following system at the edge. Our proposed cost-effective and power-efficient solution is fully-integrable with pre-existing navigation stacks and creates the foundations for the development of fully-autonomous and self-contained service robotics applications.

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“…Point Q is on the projection of the segmented image of the marker on the image plane with the measured distance of �� y 2 1 + y 2 2 . e similarity relationship between the actual image and the projected image can be written as…”

Section: Design For Artificialmentioning

confidence: 99%

“…One of the common types of service robotics is a person following robot, which has found applications in several fields such as security, surveillance, and elderly monitoring [1,2]. A nurse following robot can efficiently reduce the workload for nurses and health delivery system [3].…”

Section: Introductionmentioning

confidence: 99%

Toward Design of a Drip-Stand Patient Follower Robot

Payandeh

2020

Journal of Robotics

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A person following robot is an application of service robotics that primarily focuses on human-robot interaction, for example, in security and health care. This paper explores some of the design and development challenges of a patient follower robot. Our motivation stemmed from common mobility challenges associated with patients holding on and pulling the medical drip stand. Unlike other designs for person following robots, the proposed design objectives need to preserve as much as patient privacy and operational challenges in the hospital environment. We placed a single camera closer to the ground, which can result in a narrower field of view to preserve patient privacy. Through a unique design of artificial markers placed on various hospital clothing, we have shown how the visual tracking algorithm can determine the spatial location of the patient with respect to the robot. The robot control algorithm is implemented in three parts: (a) patient detection; (b) distance estimation; and (c) trajectory controller. For patient detection, the proposed algorithm utilizes two complementary tools for target detection, namely, template matching and colour histogram comparison. We applied a pinhole camera model for the estimation of distance from the robot to the patient. We proposed a novel movement trajectory planner to maintain the dynamic tipping stability of the robot by adjusting the peak acceleration. The paper further demonstrates the practicality of the proposed design through several experimental case studies.

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Person Following Robot Using Selected Online Ada-Boosting with Stereo Camera

Cited by 42 publications

References 27 publications

Person-following by autonomous robots: A categorical overview

Person-following by autonomous robots: A categorical overview

A Cost-Effective Person-Following System for Assistive Unmanned Vehicles with Deep Learning at the Edge

Toward Design of a Drip-Stand Patient Follower Robot

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