Accurate three-dimensional (3D) localization within indoor environments is crucial for enhancing item-based application services, yet current systems often struggle with localization accuracy and height estimation. This study introduces an advanced 3D localization system that integrates updated ultra-wideband (UWB) sensors and dual barometric pressure (BMP) sensors. Utilizing three fixed UWB anchors, the system employs geometric modeling and Kalman filtering for precise tag 3D spatial localization. Building on our previous research on indoor height measurement with dual BMP sensors, the proposed system demonstrates significant improvements in data processing speed and stability. Our enhancements include a new geometric localization model and an optimized Kalman filtering algorithm, which are validated by a high-precision motion capture system. The results show that the localization error is significantly reduced, with height accuracy of approximately ±0.05 m, and the Root Mean Square Error (RMSE) of the 3D localization system reaches 0.0740 m. The system offers expanded locatable space and faster data output rates, delivering reliable performance that supports advanced applications requiring detailed 3D indoor localization.

This paper presents a novel algorithm that enhances the efficiency of robotic manipulation by enabling the robot to reach its target with fewer obstacles being removed, thus leading to faster performance times. The challenges faced by robotic manipulation in complex and cluttered environments (e.g., supermarkets, factories, etc.), where changes are constantly occurring, are well-known. To tackle these challenges, the robot should generate a collision-free path to reach the target while requiring minimal obstacle relocation to improve task efficiency. To achieve this, the proposed task planning algorithm incorporates the Rapidly-exploring Random Tree (RRT) algorithm and a modified Vector Field Histogram Plus (VFH+). The algorithm was tested in simulated service domain environments with objects placed on shelves followed by real-robot experiments. In both experiments, the results of the proposed algorithm demonstrated a lower number of obstacle removals (up to 37%) and consequently faster performance times compared to other existing methods (improved by up to 36%). Thus, the results showed that the proposed algorithm reduces the number of obstacle relocations and improves performance time compared to existing methods. As a result, the proposed method was evaluated as an improvement in task efficiency over previous approaches and has significant implications for the use of robotic manipulation in service domains with cluttered environments.

This article [1] has been retracted at the request of the corresponding author due to a procedural oversight in the ethics review process. The human-subjec

This paper proposes a novel operation for controlling a mobile robot using a head-mounted device. Conventionally, robots are operated using computers or a joystick, which creates limitations in usability and flexibility because control equipment has to be carried by hand. This lack of flexibility may prevent workers from multitasking or carrying objects while operating the robot. To address this limitation, we propose a hands-free method to operate the mobile robot with a human gaze in an Augmented Reality (AR) environment. The proposed work is demonstrated using the HoloLens 2 to control the mobile robot, Robotnik Summit-XL, through the eye-gaze in AR. Stable speed control and navigation of the mobile robot were achieved through admittance control which was calculated using the gaze position. The experiment was conducted to compare the usability between the joystick and the proposed operation, and the results were validated through surveys (i.e., SUS, SEQ). The survey results from the participants after the experiments showed that the wearer of the HoloLens accurately operated the mobile robot in a collaborative manner. The results for both the joystick and the HoloLens were marked as easy to use with above-average usability. This suggests that the HoloLens can be used as a replacement for the joystick to allow hands-free robot operation and has the potential to increase the efficiency of human-robot collaboration in situations when hands-free controls are needed.