Prediction of Human Trajectory Following a Haptic Robotic Guide Using Recurrent Neural Networks

Social intelligence is an important requirement for enabling robots to collaborate with people. In particular, human path prediction is an essential capability for robots in that it prevents potential collision with a human and allows the robot to safely make larger movements. In this paper, we present a method for predicting the trajectory of a human who follows a haptic robotic guide without using sight, which is valuable for assistive robots that aid the visually impaired. We apply a deep learning method based on recurrent neural networks using multimodal data: (1) human trajectory, (2) movement of the robotic guide, (3) haptic input data measured from the physical interaction between the human and the robot, (4) human depth data. We collected actual human trajectory and multimodal response data through indoor experiments. Our model outperformed the baseline result while using only the robot data with the observed human trajectory, and it shows even better results when using additional haptic and depth data.Comment: 6 pages, Submitted to IEEE World Haptics Conference 201

A Preliminary Study of Machine-Learning-Based Ranging with LTE Channel Impulse Response in Multipath Environment

Alternative navigation technology to global navigation satellite systems (GNSSs) is required for unmanned ground vehicles (UGVs) in multipath environments (such as urban areas). In urban areas, long-term evolution (LTE) signals can be received ubiquitously at high power without any additional infrastructure. We present a machine learning approach to estimate the range between the LTE base station and UGV based on the LTE channel impulse response (CIR). The CIR, which includes information of signal attenuation from the channel, was extracted from the LTE physical layer using a software-defined radio (SDR). We designed a convolutional neural network (CNN) that estimates ranges with the CIR as input. The proposed method demonstrated better ranging performance than a received signal strength indicator (RSSI)-based method during our field test.Comment: Submitted to IEEE/IEIE ICCE-Asia 202

Low-Cost GNSS Simulators with Wireless Clock Synchronization for Indoor Positioning

In regions where global navigation satellite systems (GNSS) signals are unavailable, such as underground areas and tunnels, GNSS simulators can be deployed for transmitting simulated GNSS signals. Then, a GNSS receiver in the simulator coverage outputs the position based on the received GNSS signals (e.g., Global Positioning System (GPS) L1 signals in this study) transmitted by the corresponding simulator. This approach provides periodic position updates to GNSS users while deploying a small number of simulators without modifying the hardware and software of user receivers. However, the simulator clock should be synchronized to the GNSS satellite clock to generate almost identical signals to the live-sky GNSS signals, which is necessary for seamless indoor and outdoor positioning handover. The conventional clock synchronization method based on the wired connection between each simulator and an outdoor GNSS antenna causes practical difficulty and increases the cost of deploying the simulators. This study proposes a wireless clock synchronization method based on a private time server and time delay calibration. Additionally, we derived the constraints for determining the optimal simulator coverage and separation between adjacent simulators. The positioning performance of the proposed GPS simulator-based indoor positioning system was demonstrated in the underground testbed for a driving vehicle with a GPS receiver and a pedestrian with a smartphone. The average position errors were 3.7 m for the vehicle and 9.6 m for the pedestrian during the field tests with successful indoor and outdoor positioning handovers. Since those errors are within the coverage of each deployed simulator, it is confirmed that the proposed system with wireless clock synchronization can effectively provide periodic position updates to users where live-sky GNSS signals are unavailable.Comment: Submitted to IEEE Acces

Performance Comparison of Numerical Optimization Algorithms for RSS-TOA-Based Target Localization

The maximum likelihood (ML) estimator can be applied to localize a target mobile device using the RSS and TOA. However, the ML estimator for the RSS-TOA-based target localization problem is nonconvex and nonlinear, having no analytical solution. Therefore, the ML estimator should be solved numerically, unless it is relaxed into a convex or linear form. This study investigates the target localization performance and computational complexity of numerical methods for solving an ML estimator. The three widely used numerical methods are: grid search, gradient descent, and particle swarm optimization. In the experimental evaluation, the grid search yielded the lowest target localization root-mean-squared error; however, the 95th percentile error of the grid search was larger than those of the other two algorithms. The average code computation time of the grid search was extremely large compared with those of the other two algorithms, and gradient descent exhibited the lowest computation time.Comment: Submitted to the 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring

Sample-Efficient Training of Robotic Guide Using Human Path Prediction Network

Training a robot that engages with people is challenging, because it is expensive to involve people in a robot training process requiring numerous data samples. This paper proposes a human path prediction network (HPPN) and an evolution strategy-based robot training method using virtual human movements generated by the HPPN, which compensates for this sample inefficiency problem. We applied the proposed method to the training of a robotic guide for visually impaired people, which was designed to collect multimodal human response data and reflect such data when selecting the robot's actions. We collected 1,507 real-world episodes for training the HPPN and then generated over 100,000 virtual episodes for training the robot policy. User test results indicate that our trained robot accurately guides blindfolded participants along a goal path. In addition, by the designed reward to pursue both guidance accuracy and human comfort during the robot policy training process, our robot leads to improved smoothness in human motion while maintaining the accuracy of the guidance. This sample-efficient training method is expected to be widely applicable to all robots and computing machinery that physically interact with humans

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Department of Urban and Environmental Engineering (Environmental Science and Engineering )Various recalcitrant organic pollutants in water have become a worldwide concern and advanced oxidation processes (AOPs) have been suggested as an effective solution to control these compounds. However, the processes usually require an excess amount of energy for water treatment. Among the AOPs, a photocatalytic reaction has received huge attention due to the simultaneous reaction of energy production and water treatment, ideally. Most of the photocatalysts for water treatment only can utilize UV-light energy in the sunlight. However, visible light occupies the largest part of the total irradiance spectrum of sunlight. Therefore, many researchers have tried to change band level to utilize a huge amount of visible light energy. A variety of approaches have been attempted to extend the range of light spectrum available for photocatalysts activation to the visible-light region, including metal and non-metal doping, dye photosensitization, and ligand to metal charge transfer (LMCT), etc. This study investigated the visible light active photocatalysis and its hybrid systems with Fenton-like reaction for degradation of organic pollutants. Several visible light active photocatalysts (Am-peroxo-titania, S-TiO2, and g-C3N4-AQ) were synthesized and the photochemical activities for the oxidation of organic compounds were examined. Firstly, amorphous peroxo-titania (denoted as Am-peroxo-TiO2), synthesized in this study by a facile method, demonstrated photochemical activity for the oxidation of organic pollutants under visible light illumination (?? > 400 nm). Am-peroxo-TiO2 was synthesized by a one-step sol-gel method using titanium isopropoxide and hydrogen peroxide (H2O2) at room temperature and atmospheric pressure. The material produced was a yellow powdered precipitate; the measurement of diffuse reflectance confirmed light absorption of up to 600 nm. High-resolution transmission electron microscopy (HRTEM) revealed that Am-peroxo-TiO2 forms aggregates of small nanoparticles (ca < 10 nm). The surface peroxo-groups (Ti-OOH or Ti-OO-Ti) were characterized by Fourier-transform infrared spectroscopy (FT-IR) and X-ray photoelectron spectroscopy (XPS). Visible light-illuminated Am-peroxo-TiO2 completely degraded 10 ???M 4-chlorophenol (4-CP) in 4 h. The photochemical activity of Am-peroxo-TiO2 was selective to the target organic compound. Experiments using scavengers and probes of reactive oxidants revealed that reactive oxygen species such as hydroxyl and superoxide radicals are not responsible for the degradation of organic compounds. Liquid chromatography-mass spectrometry showed that 4-CP was oxidized to produce 4-chlorocatechol, hydroquinone, and benzoquinone as primary products. The results suggest that oxidation is initiated by electron abstraction or hydroxylation by the photogenerated reactive intermediates on the peroxo surface. Am-peroxo-TiO2 was stable under both dark and illuminated conditions in the absence of organic compounds. Importantly, in the presence of organic compounds, the photochemical activity of Am-peroxo-TiO2 gradually decreased. Further, platinization enhanced the photochemical activity as well as the stability of Am-peroxo-TiO2. Secondly, sulfur doped TiO2 (denoted as S-TiO2) demonstrated its visible light photocatalytic activity with Fenton-like reagents (Fe(III) and H2O2) for degradation of organic compounds. S-TiO2 exhibited a small rectangular-shaped crystalline structure which is composed of the mixture of anatase and rutile crystalline phases. FT-IR and X-ray fluorescence (XRF) analysis confirmed Ti-O-S on the surface of S-TiO2. In photochemical activity, visible light-illuminated S-TiO2/Fe(III) system completely degraded 10 ??M 4-chlorophenol (4-CP) within 2 h. The photochemical activity of S-TiO2/Fe(III) limited within pH 3.0 and was selective in degradation of the organic compound. Experiments using radical scavengers and oxidant probes revealed that the oxidation by photogenerated holes is responsible for the degradation of organic compounds by illuminated S-TiO2/Fe(III) and the role of ???OH is negligible. Meanwhile, visible light-illuminated S-TiO2/Fe(III)/H2O2 system effectively degraded 10 ??M benzoic acid in 1h. The photochemical activity of S-TiO2/Fe(III)/H2O2 also limited within pH 3.0 and was non-selective in degradation of the organic compound. Experiments using radical scavengers and oxidant probes revealed that ???OH is mainly responsible for the degradation of organic compounds by illuminated S-TiO2/Fe(III)/H2O2. The repeated use of S-TiO2/Fe(III) system decreased the photocatalytic activity for the 4-CP degradation, however, that of S-TiO2/Fe(III)/H2O2 system maintained the photocatalytic activity for the BA degradation. Lastly, anthraquinone anchored graphitic carbon nitride (denoted as g-C3N4-AQ), reported in the photochemical production of H2O2, demonstrated its visible light photocatalytic activity with Fe(III) for degradation of organic compounds. g-C3N4-AQ exhibited similar crystallinity and light absorption spectrum with the pristine g-C3N4. FT-IR and XPS confirmed the covalent bonds between AQ and g-C3N4. The visible light illuminated g-C3N4-AQ/Fe(III) showed different photochemical activities in accordance with the existence of dissolved oxygen. In visible light illuminated g-C3N4-AQ/Fe(III), experiments using various target organic compounds, radical scavengers, and oxidant probes elucidated that ???OH is responsible for the degradation of organic compounds in the presence of dissolved oxygen, however, hole is the main oxidant in the absence of dissolved oxygen.clos