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Papers by randa almadhoun

Journal of Mechanisms and Robotics, 2020

In this paper, a novel dual-UAV collaborative aerial transport strategy based on energy distribut... more In this paper, a novel dual-UAV collaborative aerial transport strategy based on energy distribution and load sharing is proposed. This paper presents the first experimental demonstration of dual-UAV collaborative aerial transport while distributing power consumption. The demonstration is performed while distributing the power consumption between two drones sharing a load based on their battery state of charge. A numerical model of the dual-hex-rotor-payload is used to validate the proposed strategy. Numerical and hardware tests were conducted to demonstrate the load distribution using multiple UAV with certain spatial configurations. Finally, collaborative aerial transport test scenarios are performed numerically and experimentally. The simulation and experimental results show the effectiveness and applicability of the proposed strategy.

SN Applied Sciences, 2019

There has been an increasing interest in researching, developing and deploying multi-robot system... more There has been an increasing interest in researching, developing and deploying multi-robot systems. This has been driven mainly by: the maturity of the practical deployment of a single-robot system and its ability to solve some of the most challenging tasks. Coverage path planning (CPP) is one of the active research topics that could benefit greatly from multi-robot systems. In this paper, we surveyed the research topics related to multi-robot CPP for the purpose of mapping and model reconstructions. We classified the topics into: viewpoints generation approaches; coverage planning strategies; coordination and decision-making processes; communication mechanism and mapping approaches. This paper provides a detailed analysis and comparison of the recent research work in this area, and concludes with a critical analysis of the field, and future research perspectives.

International Journal of Advanced Robotic Systems, 2016

Advancements in robotics and autonomous systems are being deployed nowadays in many application d... more Advancements in robotics and autonomous systems are being deployed nowadays in many application domains such as search and rescue, industrial automation, domestic services and healthcare. These systems are developed to tackle tasks in some of the most challenging, labour intensive and dangerous environments. Inspecting structures (e.g. bridges, buildings, ships, wind turbines and aircrafts) is considered a hard task for humans to perform and of critical importance since missing any details could affect the structure’s performance and integrity. Additionally, structure inspection is time and resource intensive and should be performed as efficiently and accurately as possible. Inspecting various structures has been reported in the literature using different robotic platforms to: inspect difficult to reach areas and detect various types of faults and anomalies. Typically, inspection missions involve performing three main tasks: coverage path planning, shape, model or surface reconstruc...

In this paper, we propose a coverage planning algorithm for inspecting an aircraft, using an Unma... more In this paper, we propose a coverage planning algorithm for inspecting an aircraft, using an Unmanned Ariel Vehicle (UAV). Inspecting structures (e.g. bridges, buildings, ships, wind turbines, aircrafts) is considered a hard task for humans to perform, and of critical nature since missing any detail could affect the structure’s performance and integrity. Additionally, structure inspection is a time and resource intensive task that should be performed as efficiently and accurately as possible. In this paper we introduce a search space coverage path planner (SSCPP) with a heuristic reward function that exploits our knowledge of the structure model, and the UAV’s onboard sensors’ models to generate resolution optimal paths that maximizes coverage. The proposed method follows a model based coverage path planning approach to generate an optimized path that passes through a set of admissible waypoints to fully cover a complex structure. The algorithm predicts the coverage percentage by us...

IEEE Access

Coverage Path Planning (CPP) is an essential capability for autonomous robots operating in variou... more Coverage Path Planning (CPP) is an essential capability for autonomous robots operating in various critical applications such as fire fighting, and inspection. Performing autonomous coverage using a single robot system consumes time and energy. In particular, 3D large structures might contain some complex and occluded areas that shall be scanned rapidly in certain application domains. In this paper, a new Hybrid Coverage Path Planning (HCPP) approach is proposed to explore and cover unknown 3D large structures using a decentralized multi-robot system. The HCPP approach combines a guided Next Best View (NBV) approach with a developed Long Short Term Memory (LSTM) waypoint prediction approach to decrease the CPP exploration time at each iteration and simultaneously achieve high coverage. The hybrid approach is the new ML paradigm which fosters intelligence by balancing between data efficiency and generality allowing the exchange of some CPP parts with a learned model. The HCPP uses a stateful LSTM network architecture which is trained based on collected paths that cover different 3D structures to predict the next viewpoint. This architecture captures the dynamic dependencies of adjacent viewpoints in the long term sequences like the coverage paths. The HCPP switches between these methods triggered by either the number of iterations or an entropy threshold. In the decentralized multi-robot system, the proposed HCPP is embedded in each robot where each one of them shares its global 3D map ensuring robustness. The results performed in a realistic Gazebo robotic simulator confirmed the advantage of the proposed HCPP approach by achieving high coverage on different 3D unknown structures in a shorter time compared to conventional NBV.

The most critical process in the inspection is the structure coverage which is a time and resourc... more The most critical process in the inspection is the structure coverage which is a time and resource intensive task. In this paper, Search Space Coverage Path Planning (SSCPP) algorithm for inspecting complex structure using a vehicular system consisting of Unmanned Aerial Vehicle (UAV) is proposed. The proposed algorithm exploits our knowledge of the structure model, and the UAV’s onboard sensors to generate coverage paths that maximizes coverage and accuracy. The algorithm supports the integration of multiple sensors to increase the coverage at each viewpoint and reduce the mission time. A weighted heuristic reward function is developed in the algorithm to target coverage, accuracy, travelled distance and turning angle at each viewpoint. The iterative processes of the proposed algorithm were accelerated exploiting the parallel architecture of the Graphics Processing Unit (GPU). A set of experiments using models of different shapes were conducted in simulated and real environments. T...

2016 IEEE 59th International Midwest Symposium on Circuits and Systems (MWSCAS)

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA)

These days, IoT devices are deployed at a massive scale, with Cisco predicting 20 billion devices... more These days, IoT devices are deployed at a massive scale, with Cisco predicting 20 billion devices by the year 2020. As opposed to endpoint devices, IoT devices are resource-constrained devices, incapable of securing and defending themselves, and can be easily hacked and compromised. Fog computing can augment such capacity limitations by providing localized compute, storage, and networking for a group of IoT devices. As fog nodes are deployed in close proximity to IoT devices, fog computing can be more effective than cloud computing. Furthermore, Blockchain has emerged as technology with capabilities to provide secure management, authentication and access to IoT devices and their data, in decentralized manner with high trust, integrity, and resiliency. In this paper, we propose a user authentication scheme using blockhain-enabled fog nodes in which fog nodes interface to Ethereum smart contracts to authenticate users to access IoT devices. The fog nodes are used to provide scalability to the system by relieving the IoT devices from carrying out heavy computation involving tasks related to authentication and communicating with the blockchain. We describe system components, architecture and design, and we discuss key aspects related to security analysis, functionality, testing and implementation of the smart contracts. The full code of the smart contracts for authentication registry, lists, rules and logic is also made publicly available at Github.

Remote Sensing

In this paper, a Next Best View (NBV) approach with a profiling stage and a novel utility functio... more In this paper, a Next Best View (NBV) approach with a profiling stage and a novel utility function for 3D reconstruction using an Unmanned Aerial Vehicle (UAV) is proposed. The proposed approach performs an initial scan in order to build a rough model of the structure that is later used to improve coverage completeness and reduce flight time. Then, a more thorough NBV process is initiated, utilizing the rough model in order to create a dense 3D reconstruction of the structure of interest. The proposed approach exploits the reflectional symmetry feature if it exists in the initial scan of the structure. The proposed NBV approach is implemented with a novel utility function, which consists of four main components: information theory, model density, traveled distance, and predictive measures based on symmetries in the structure. This system outperforms classic information gain approaches with a higher density, entropy reduction and coverage completeness. Simulated and real experiments ...