People-following system design for mobile robots using kinect sensor

Gao, Xing; Shuangna, Tian; Sun, Hexu; Liu, Weipeng; Liu, Huawang

doi:10.1109/ccdc.2013.6561495

Cited by 24 publications

(9 citation statements)

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“…9. According to the image principle explained in [4,11], the heading angle error e between the center of detected object and the center ofRGB image is given by, e=arctan ( 7), eE (-50°,50°)…”

Section: ) Heading Angle Errormentioning

confidence: 99%

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Object following control of six-legged robot using Kinect camera

Gulalkari

Hoang

Pratama

et al. 2014

2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

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This paper proposes a vision-based object following system for the six-legged robot using Kinect camera. To do this task, the followings are done. First, for image processing, a Kinect camera is installed on the six-legged robot. The interesting moving object is detected by a color-based object detection method. The local coordinates of the detected object are obtained to provide the position of the object. Second, the backstepping method using Lyapunov function is adopted to design a controller for the six-legged robot to achieve object following. Finally, the simulation and experimental results are presented to show the effectiveness of the proposed control method.

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Section: ) Heading Angle Errormentioning

confidence: 99%

“…Most of these research works were implemented either on wheeled or legged mobile robots. As in [4], people following system was designed using wheeled robot. But there are certain limitations with the wheeled configuration as wheels are inefficient on irregular or rough platforms.…”

Section: Introductionmentioning

confidence: 99%

Object following control of six-legged robot using Kinect camera

Gulalkari

Hoang

Pratama

et al. 2014

2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

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“…An image-processing method [ 1 , 2 , 3 , 4 , 5 ] uses a different type or number of cameras and algorithms for obtaining the user’s location and motion information. By analyzing images, it identifies the human’s location and steers itself after the human.…”

Section: Related Researchmentioning

confidence: 99%

A Self-Organizing Interaction and Synchronization Method between a Wearable Device and Mobile Robot

Kim

Lee

Kang

2016

Sensors

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In the near future, we can expect to see robots naturally following or going ahead of humans, similar to pet behavior. We call this type of robots “Pet-Bot”. To implement this function in a robot, in this paper we introduce a self-organizing interaction and synchronization method between wearable devices and Pet-Bots. First, the Pet-Bot opportunistically identifies its owner without any human intervention, which means that the robot self-identifies the owner’s approach on its own. Second, Pet-Bot’s activity is synchronized with the owner’s behavior. Lastly, the robot frequently encounters uncertain situations (e.g., when the robot goes ahead of the owner but meets a situation where it cannot make a decision, or the owner wants to stop the Pet-Bot synchronization mode to relax). In this case, we have adopted a gesture recognition function that uses a 3-D accelerometer in the wearable device. In order to achieve the interaction and synchronization in real-time, we use two wireless communication protocols: 125 kHz low-frequency (LF) and 2.4 GHz Bluetooth low energy (BLE). We conducted experiments using a prototype Pet-Bot and wearable devices to verify their motion recognition of and synchronization with humans in real-time. The results showed a guaranteed level of accuracy of at least 94%. A trajectory test was also performed to demonstrate the robot’s control performance when following or leading a human in real-time.

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“…Robotic applications for health care are having a very significant growth over the past decade [1]. Human-Robot Interaction (HRI) aims at comprehending, building, and evaluating robotic systems to be used by humans, or to cooperate with them, and that interact with humans in meaningful ways [2].…”

Section: Introductionmentioning

confidence: 99%

Human-driven multi-robot design process for social interactions with children on complex environments

Gonçalves

Arsénio

2015

2015 6th International Conference on Automation, Robotics and Applications (ICARA)

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Robots have been traditionally in operation away from people, for instance in industrial environments. More recently, there has been a trend for bringing robots to market for helping people. In particular, children constitute a challenging group for robot interaction, due to their curiosity and energy, as well as safety concerns. This paper describes the construction process of an external structure for a fleet of mobile robots designed for interactions with children in a hospital environment. We address several challenges on the design process, critical for the robots to be able to operate safely, while interacting socially, among a group of children with specific needs.

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People-following system design for mobile robots using kinect sensor

Cited by 24 publications

References 1 publication

Object following control of six-legged robot using Kinect camera

Object following control of six-legged robot using Kinect camera

A Self-Organizing Interaction and Synchronization Method between a Wearable Device and Mobile Robot

Human-driven multi-robot design process for social interactions with children on complex environments

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