Analysis and Accuracy Improvement of UWB-TDoA-Based Indoor Positioning System

Positioning systems are used in a wide range of applications which require determining the position of an object in space, such as locating and tracking assets, people and goods; assisting navigation systems; and mapping. Indoor Positioning Systems (IPSs) are used where satellite and other outdoor positioning technologies lack precision or fail. Ultra-WideBand (UWB) technology is especially suitable for an IPS, as it operates under high data transfer rates over short distances and at low power densities, although signals tend to be disrupted by various objects. This paper presents a comprehensive study of the precision, failure, and accuracy of 2D IPSs based on UWB technology and a pseudo-range multilateration algorithm using Time Difference of Arrival (TDoA) signals. As a case study, the positioning of a 4×4m2 area, four anchors (transceivers), and one tag (receiver) are considered using bitcraze’s Loco Positioning System. A Cramér–Rao Lower Bound analysis identifies the convex hull of the anchors as the region with highest precision, taking into account the anisotropic radiation pattern of the anchors’ antennas as opposed to ideal signal distributions, while bifurcation envelopes containing the anchors are defined to bound the regions in which the IPS is predicted to fail. This allows the formulation of a so-called flyable area, defined as the intersection between the convex hull and the region outside the bifurcation envelopes. Finally, the static bias is measured after applying a built-in Extended Kalman Filter (EKF) and mapped using a Radial Basis Function Network (RBFN). A debiasing filter is then developed to improve the accuracy. Findings and developments are experimentally validated, with the IPS observed to fail near the anchors, precision around ±3cm, and accuracy improved by about 15cm for static and 5cm for dynamic measurements, on average

Development of a PID Controlled Arduino-Based Stabiliser

Inverted pendulum remained as the most popular topic for control theory researches because of its characteristic of being non-linear, unstable and under-actuated system. It is ideal for verification, validation and enhancement of control theory by stabilizing the inverted pendulum in an upright position using various controller and stabilizer mechanism. For this project, Proportional-Integral-Derivative (PID) controller is used to stabilize the inverted pendulum by tuning the respective gains (kP, kI, and kD) to control the parameters of inverted pendulum which includes the rise time, settling time, overshoot and steady-state error in cooperation with of Arduino microcontroller. The objective of this project is to design and build a stabilizer mechanism with the integration of mechanical and electrical components to stabilize two Directional (2D) inverted pendulum similar to 3D printer mechanism. Besides that, PID controller will be tuned in Arduino microcontroller and control the output of stabilizer mechanism. The stabilizer mechanism is designed in SolidWorks software and built using various manufacturing techniques, raw materials and 3D printing, while the electronics components such as gyroscope and Direct Current (DC) motors are controlled using Arduino Due in C++ language. The gyroscope determines the tilting angle of the pendulum as a feedback in the control loop, and the gains of PID are used to control the speed and direction of DC motor to provide sufficient force/torque to keep the inverted pendulum in an upright position. The stabilizer mechanism with inverted pendulum has been built and the gains of PID have been tuned using “trial and error” method as friction is now taken into consideration. The inverted pendulum is successfully stabilized in an upright position (0o measure at z-axis) using control theory

Some Supervision Required: Incorporating Oracle Policies in Reinforcement Learning via Epistemic Uncertainty Metrics

An inherent problem of reinforcement learning is performing exploration of an environment through random actions, of which a large portion can be unproductive. Instead, exploration can be improved by initializing the learning policy with an existing (previously learned or hard-coded) oracle policy, offline data, or demonstrations. In the case of using an oracle policy, it can be unclear how best to incorporate the oracle policy's experience into the learning policy in a way that maximizes learning sample efficiency. In this paper, we propose a method termed Critic Confidence Guided Exploration (CCGE) for incorporating such an oracle policy into standard actor-critic reinforcement learning algorithms. More specifically, CCGE takes in the oracle policy's actions as suggestions and incorporates this information into the learning scheme when uncertainty is high, while ignoring it when the uncertainty is low. CCGE is agnostic to methods of estimating uncertainty, and we show that it is equally effective with two different techniques. Empirically, we evaluate the effect of CCGE on various benchmark reinforcement learning tasks, and show that this idea can lead to improved sample efficiency and final performance. Furthermore, when evaluated on sparse reward environments, CCGE is able to perform competitively against adjacent algorithms that also leverage an oracle policy. Our experiments show that it is possible to utilize uncertainty as a heuristic to guide exploration using an oracle in reinforcement learning. We expect that this will inspire more research in this direction, where various heuristics are used to determine the direction of guidance provided to learning.Comment: Under review at TML

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Shimmy: Gymnasium and PettingZoo Wrappers for Commonly Used Environments

An API conversion tool providing Gymnasium and PettingZoo bindings for popular external reinforcement learning environments.</span

Development of a PID Controlled Arduino-Based Stabiliser

Inverted pendulum remained as the most popular topic for control theory researches because of its characteristic of being non-linear, unstable and under-actuated system. It is ideal for verification, validation and enhancement of control theory by stabilizing the inverted pendulum in an upright position using various controller and stabilizer mechanism. For this project, Proportional-Integral-Derivative (PID) controller is used to stabilize the inverted pendulum by tuning the respective gains (kP, kI, and kD) to control the parameters of inverted pendulum which includes the rise time, settling time, overshoot and steady-state error in cooperation with of Arduino microcontroller. The objective of this project is to design and build a stabilizer mechanism with the integration of mechanical and electrical components to stabilize two Directional (2D) inverted pendulum similar to 3D printer mechanism. Besides that, PID controller will be tuned in Arduino microcontroller and control the output of stabilizer mechanism. The stabilizer mechanism is designed in SolidWorks software and built using various manufacturing techniques, raw materials and 3D printing, while the electronics components such as gyroscope and Direct Current (DC) motors are controlled using Arduino Due in C++ language. The gyroscope determines the tilting angle of the pendulum as a feedback in the control loop, and the gains of PID are used to control the speed and direction of DC motor to provide sufficient force/torque to keep the inverted pendulum in an upright position. The stabilizer mechanism with inverted pendulum has been built and the gains of PID have been tuned using "trial and error" method as friction is now taken into consideration. The inverted pendulum is successfully stabilized in an upright position (0o measure at z-axis) using control theory.</p