Probabilistic models for robot-based object segmentation

This paper introduces a novel probabilistic method for robot based object segmentation. The method integrates knowledge of the robot’s motion to determine the shape and location of objects. This allows a robot with no prior knowledge of its workspace to isolate objects against their surroundings by moving them and observing their visual feedback. The main contribution of the paper is to improve upon current methods by allowing object segmentation in changing environments and moving backgrounds. The approach allows optimal values for the algorithm parameters to be estimated. Empirical studies against alternatives demonstrate clear improvements in both planar and three dimensional motion.     

Robust camera pose and scene structure analysis for service robotics

Successful path planning and object manipulation in service robotics applications rely both on a good estimation of the robot’s position and orientation (pose) in the environment, as well as on a reliable understanding of the visualized scene. In this paper a robust real-time camera pose and a scene structure estimation system is proposed. First, the pose of the camera is estimated through the analysis of the so-called tracks. The tracks include key features from the imaged scene and geometric constraints which are used to solve the pose estimation problem. Second, based on the calculated pose of the camera, i.e. robot, the scene is analyzed via a robust depth segmentation and object classification approach. In order to reliably segment the object’s depth, a feedback control technique at an image processing level has been used with the purpose of improving the robustness of the robotic vision system with respect to external influences, such as cluttered scenes and variable illumination conditions. The control strategy detailed in this paper is based on the traditional open-loop mathematical model of the depth estimation process. In order to control a robotic system, the obtained visual information is classified into objects of interest and obstacles. The proposed scene analysis architecture is evaluated through experimental results within a robotic collision avoidance system.     

Coping behaviors in short message service (SMS)-based disaster alert systems: From the lens of protection motivation theory as elaboration likelihood

Short message service (SMS)-based disaster alert systems are used as critical methods that inform people of natural disasters. This study investigates how two different decision-making routes influence adaptive copings based upon users’ protection motivations. The two important routes, argument quality and source credibility, are presented as focal antecedents of coping adaptiveness. And perceived threat and coping efficacy are tested as a moderator as elaboration likelihood. To achieve these goals, we propose a theoretical framework and analyze survey data to test the hypotheses. The results illustrate that two elaboration likelihood variables show significant moderating roles in the proposed research model.     

Using subject-specific three-dimensional (3D) anthropometry data in digital human modelling: case study in hand motion simulation

Digital human modelling enables ergonomists and designers to consider ergonomic concerns and design alternatives in a timely and cost-efficient manner in the early stages of design. However, the reliability of the simulation could be limited due to the percentile-based approach used in constructing the digital human model. To enhance the accuracy of the size and shape of the models, we proposed a framework to generate digital human models using three-dimensional (3D) anthropometric data. The 3D scan data from specific subjects’ hands were segmented based on the estimated centres of rotation. The segments were then driven in forward kinematics to perform several functional postures. The constructed hand models were then verified, thereby validating the feasibility of the framework. The proposed framework helps generate accurate subject-specific digital human models, which can be utilised to guide product design and workspace arrangement.

Practitioner Summary: Subject-specific digital human models can be constructed under the proposed framework based on three-dimensional (3D) anthropometry. This approach enables more reliable digital human simulation to guide product design and workspace arrangement.