Online Boosting-Based Target Identification among Similar Appearance for Person-Following Robots.

It is challenging for a mobile robot to follow a specific target person in a dynamic environment, comprising people wearing similar-colored clothes and having the same or similar height. This study describes a novel framework for a person identification model that identifies a target person by merging multiple features into a single joint feature online. The proposed framework exploits the deep learning output to extract four features for tracking the target person without prior knowledge making it generalizable and more robust. A modified intersection over union between the current frame and the last frame is proposed as a feature to distinguish people, in addition to color, height, and location. To improve the performance of target identification in a dynamic environment, an online boosting method was adapted by continuously updating the features in every frame. Through extensive real-life experiments, the effectiveness of the proposed method was demonstrated by showing experimental results that it outperformed the previous methods.

Deep-Learning-Based Indoor Human Following of Mobile Robot Using Color Feature.

Human following is one of the fundamental functions in human-robot interaction for mobile robots. This paper shows a novel framework with state-machine control in which the robot tracks the target person in occlusion and illumination changes, as well as navigates with obstacle avoidance while following the target to the destination. People are detected and tracked using a deep learning algorithm, called Single Shot MultiBox Detector, and the target person is identified by extracting the color feature using the hue-saturation-value histogram. The robot follows the target safely to the destination using a simultaneous localization and mapping algorithm with the LIDAR sensor for obstacle avoidance. We performed intensive experiments on our human following approach in an indoor environment with multiple people and moderate illumination changes. Experimental results indicated that the robot followed the target well to the destination, showing the effectiveness and practicability of our proposed system in the given environment.

No Evidence Suggests that the Clinical Effectiveness of Conventional Occlusal Splints is Superior to That of Psychosocial Interventions for Myofascial Tempromandibular Disorders Pain.

ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: A systematic review and meta-analysis of usual treatment versus psychosocial interventions in the treatment of myofascial temporomandibular disorder pain. Fan Roldán-Barraza C, Janko S, Villanueva J, Araya I, Lauer HC. J Oral Facial Pain Headache 2014;28(3):205-22. SOURCE OF FUNDING: Self-funding TYPE OF STUDY/DESIGN: Systematic review and meta-analysis.