Fendy Santoso

Visual–Inertial Navigation Systems for Aerial Robotics: Sensor Fusion and Technology

In this paper, we comprehensively discuss the current progress of visual–inertial (VI) navigation systems and sensor fusion research with a particular focus on small unmanned aerial vehicles, known as microaerial vehicles (MAVs). Such fusion has become very topical due to the complementary characteristics of the two sensing modalities. We discuss the pros and cons of the most widely implemented VI systems against the navigational and maneuvering capabilities of MAVs. Considering the issue of optimum data fusion from multiple heterogeneous sensors, we examine the potential of the most widely used advanced state estimation techniques (both linear and nonlinear as well as Bayesian and non-Bayesian) against various MAV design considerations. Finally, we highlight several research opportunities and potential challenges associated with each technique.

3D Mapping for Visualization of Rigid Structures: A Review and Comparative Study

In this review, we discuss state-of-the-art developments in 3D models for small and rigid structures. This includes the pros and cons of cutting-edge range cameras used as active 3D scanners, while also considering passive image reconstruction schemes by means of the well-known structure-from-motion (SfM) algorithms. Furthermore, we discuss the issue of how data fusion algorithms can be used to optimally fuse 2D contour information onto 3D models for several different applications. Considering the benefits of 3D range sensors, we also review current trends in optimum data fusion of point clouds from 3D range sensors. We present the benefits and the limitations of each algorithm against various design considerations. To highlight the pros and cons, we also perform a comparative study of the performance of a 3D range sensor, represented by an iPad structure sensor, with respect to the well-known SfM software packages, namely, Bundler, Microsoft PhotoSynth, Agisoft PhotoScan, and Smart3DCapture. Last, we highlight several research opportunities and potential research challenges associated with each technique.

Indoor location-aware medical systems for smart homecare and telehealth monitoring: state-of-the-art.

This paper presents a comprehensive literature review of current progress in the application of state-of-the-art indoor positioning systems for telecare and telehealth monitoring. This review is the first in the literature that provides a comprehensive discussion on how existing wireless indoor positioning systems can benefit the development of home-based care systems. More specifically, this review provides an in-depth comparative study of how both system users and medical practitioners can get benefit from indoor positioning technologies; e.g. for real-time monitoring of patients suffering chronic cardiovascular conditions, general monitoring of activities of daily living (ADLs), fall detection systems for the elderly as well as indoor navigation systems for those suffering from visual impairments. Furthermore, it also details various aspects worth considering when choosing a certain technology for a specific healthcare application; e.g. the spatial precision demanded by the application, trade-offs between unobtrusiveness and complexity, and issues surrounding compliance and adherence with the use of wearable tags. Beyond the current state-of-the-art, this review also rigorously discusses several research opportunities and the challenges associated with each.

Modeling, Autopilot Design, and Field Tuning of a UAV With Minimum Control Surfaces

While having the benefit of mechanical simplicity, model-scale unmanned aerial vehicles with only two elevon control surfaces present interesting challenges in dynamics modeling, autopilot design, and field tuning. Because of limited on-board computing and communication bandwidth, traditional control theory was applied to systematically tune the proportional-integral-derivative-based (PID) autopilots offline. Based on the aerodynamic analysis, its multi-input, multi-output underactuated linear model configuration was deduced. Utilizing the real-time flight data collected from human-controlled test flight, a two-input three-output linear model was obtained by means of system identification. It includes the transfer functions in the airspeed loop, heading loop, and altitude loop. The dynamic behavior of the aircraft was analyzed, and five PID controllers in three loops were designed based on the root-locus techniques. The controllers were implemented and further tuned in field flights with improved performances. We demonstrate that with proper precautions, traditional control theory can be used to solve complex control problems that are often tackled with nonlinear control algorithms.

A Decentralised Self-Dispatch Algorithm for Square-Grid Blanket Coverage Intrusion Detection Systems in Wireless Sensor Networks

This research aims to propose a novel decentralised coverage protocol known as square-grid blanket coverage control algorithm for self-deployments of autonomous robotic wireless sensor networks in the open corridors as a means to discourage any intrusions. The algorithm advocates distributed solution and is asymptotically optimal in the sense of uniformity. The motion coordination scheme employed is due to the nearest neighbour technique which is implemented for the purpose of clustering and coordination among mobile sensor nodes in local area (vicinity), that is, to achieve uniform and distributed solutions for both 1-barrier coverage as an initial thrust of this research as well as our square-grid blanket coverage. Having successfully achieved 1-barrier coverage, mobile sensor nodes are subsequently moved in the systematic zigzag (snake-like) pattern by utilising local information obtained from its neighbourhoods to achieve the desired square-grid lattice. Research points out that simple motion coordination schemes have resulted in powerful, efficient and intelligent control algorithm to achieve the desired coverage. To manifest the efficacy of the proposed algorithm, several computer simulations have been conducted accordingly.

Robust μ-synthesis Loop Shaping for Altitude Flight Dynamics of a Flying-Wing Airframe

In this paper we present a centralised flight-by-wire system based on μ-synthesis approach to the longitudinal flight motion of our experimental flying wing unmanned aerial vehicle (UAV), P15035 series. The challenge associated with our UAV is related to the fact that all motions of our UAV are controlled by two independently-actuated-ailerons namely elevons, together with its throttle. The scope of this research, nonetheless, falls within the area of elevon control based on the trimmed linear longitudinal flight modes obtained experimentally while throttle was set constant. The reason for considering μ-synthesis autopilot is to minimise the effects of uncertainty in modelling by maximising the amount of tolerable uncertainty within our system’s bandwidth as we aim to minimise the structure singular value μ of the corresponding robust performance associated with the uncertain systems. Second, it also provides flexibility in tunning due to the absence of partitioning model of MIMO system. Hence the entire autopilot was designed by keeping the system model as a whole. We also perform a comparative study with respect to well-known H∞

A New Framework for Rapid Wireless Tracking Verifications Based on Optimized Trajectories in Received Signal Strength Measurements

\textbf {H}_{\infty }

Tracking-Based Wireless Intrusion Detection for Vehicular Networks

mixed sensitivity autopilot. Our study indicates that the μ synthesis autopilot designed possesses better performances both in time and frequency domain as indicated by reasonably quick settling time in the absence of overshoot while still maintaining better robust stability margin.

Range-only distributed navigation protocol for uniform coverage in wireless sensor networks

Secure physical regions (e.g., border areas, nuclear zones, or military facilities) are often patrolled by networked robotic vehicles that require the capability to rapidly verify the advertised location of a potential intruder based on received signal strengths. In this paper, we develop novel algorithms by which mobile robots can coordinate their motions in order to minimize the time required to verify the advertised location for given accuracy bounds. Our specific contributions on this paper are threefold. Firstly, we develop a framework that uses a combination of the particle filters (for position estimation) and the Cramér-Rao lower bounds (for threshold of validation) to drive the motion models for rapid verification of the reported position. We believe our approach is the first in the literature that is accurate, easy to compute, and feasible for practical implementation. Secondly, we propose a centralized coordinated motion algorithm that is optimal at each sampling time. This provides a lower bound on detection time that can be used as a benchmark for practical considerations. Thirdly, we present a practical heuristic approach that allows for distributed protocol based on the concept of the gradient vectors. Subsequently, we also advocate a sub-optimal approach, derived from our heuristic approach, which provides a good trade-off between performance and computational resources. Our results are important for the development of secure access control schemes to prevent unauthorized access of communication networks from malicious users.

Adaptive Neuro-Fuzzy Inference System identification for the dynamics of the AR.Drone Quadcopter

In this work we develop a new tracking-based wireless intrusion detection algorithm that allows for the identification of malicious vehicle network users who are not at their appropriate locations. Based on a particle filter implementation and detection thresholds set by Cramer-Rao lower bounds we show how our tracking-verification algorithm is capable of verifying any reported positions within a reasonable time frame of order 30 seconds. We explicitly determine how the performance of the algorithm, as measured by detection and false positive rates, is influenced by the amount of tracking information collected. The results presented here are important for implementation of safe vehicular networks where only users at the expected locations can access and participate in the network communications.