Verifiable Timed Signatures (VTS) are cryptographic primitives that enable the creation of a signature that can only be retrieved after a specific time delay, while also providing verifiable evidence of its existence. This framework is particularly useful in blockchain applications. Current VTS schemes rely on signature algorithms such as BLS, Schnorr, and ECDSA, which are vulnerable to quantum attacks due to the vulnerability of the discrete logarithm problem to Shor’s Algorithm. We introduce VT-UOV, a novel VTS scheme based on the Salt-Unbalanced Oil and Vinegar (Salt-UOV) Digital Signature Algorithm. As a multivariate polynomialbased cryptographic primitive, Salt-UOV provides strong security against both classical and quantum adversaries.

Verifiable Timed Signatures (VTS) are crypto-graphic constructs that enable obtaining a signature at a specific time in the future and provide evidence that the signature is legitimate. This framework particularly finds utility in applications such as payment channel networks, multiparty signing operations, or multiparty computation, especially within blockchain architectures. Currently, VTS schemes are based on signature algorithms such as BLS signature, Schnorr signature, and ECDSA. These signature algorithms are considered insecure against quantum attacks due to the effect of Shor's Algorithm on the discrete logarithm problem. We present a new VTS scheme called VT-Dilithium based on CRYSTALS-Dilithium Digital Signature Algorithm that has been selected as NIST's quantum-resistant digital signature standard and is considered secure against both classical and quantum attacks. Integrating Dilithium into the VTS scheme is a more challenging problem due to its complex mathematical operations (i.e. polynomial multiplications, rounding operations) and large module param-eters such as polynomials, polynomial vectors, and matrices. This work aims to provide a comprehensive exposition of VT-Dilithium scheme.

Simultaneous Localization and Mapping (SLAM) is a probabilistic approach that builds the map of an unknown environment and estimate the position of the agent within that map at the same time. SLAM has three assumptions to be able to work properly; the environment must be suitable for data acquisition (illumination, textured, etc.), the data that is received from the sensors must be overlapping partially in consecutive frames and the static environment must be dominated over the dynamic environment.The last autonomous robotics applications have a lot of impacts to our lifes. They already started to work in the indoor and out-door environments (warehouse, caffe, street etc). Most of the use cases of the robots can provide the first two assumptions which is mentioned in the last paragraph. But the third assumption which is related with dynamic objects can be easily violated when the use of robots in dynamic environments with moving objects.In this work, we focused on the decreasing the negative impact of dynamic objects to SLAM accuracy. For this, we developed RGBD SLAM solution that can live with the dynamic objects. The main workflow of the solution assumes visual features that are obtained from dynamic objects as outliers. We used open source version of the ORB-SLAM3 as a base software for RGBD SLAM. We integrated YOLOv3 model to our solution to detect the dynamic objects in RGB frames. We selected ORB-SLAM3 and YOLOv3 applications for success of the algorithms. Also they can work at high frequency which means that they can work in real life applications.In this work, we observed 82% improvement on average in the TUM “wallking” datasets. By elimination of the outliers, the accuracy of the SLAM algorithm is increased. Also the robustness of the system against to the dynamic objects is increased.

National Institute of Standards and Technology (NIST) initiated a post-quantum standardization process in 2016, and as of July 2020, Round 3 candidates were announced. Among these candidates, Crystals-Kyber and Crystals-Dilithium are the most promising lattice-based key encapsulation mechanism (KEM) and signature algorithm that rely on the module learning with errors (Module-LWE) problem. In general, polynomial multiplication is one of the most time-consuming operations in Module-LWE based cryptosystems. There are several polynomial multiplication methods for multiplying two polynomials effectively. One of the most efficient methods is Number Theoretic Transform (NTT). This paper analyzes the number of arithmetic operations occupied in NTT multiplication for Kyber and Dilithium cryptosystems. The general formula on the number of multiplications and additions used in NTT operation for the lattice-based algorithms which have a ring structure similar to Kyber and Dilithium is given for$q < 2^{w-1}$where$w$is the word size and$q$is the modulus. Also, cycle counts of arithmetic operations of Kyber and Dilithium are calculated on reference implementations to determine the relationship between our formulations and cycle counts.

Design and development of legged robots that can navigate effectively and autonomously in a wide range of environments is a challenging problem. At that point it should be noted that nature inspired optimization techniques have been widely studied for autonomous navigation of legged robots. In this study the framework constructed for six-legged walking behavior generation using genetic algorithms is presented and simulation results on Unity are discussed.

Detection of thermal targets for search and rescue robots is very important to be able to save more lives. Because the living human body is at a certain temperature, each thermal target point implies possible victim. Robots produced for search and rescue are expected to be able to perceive and steer toward the thermal targets. The focus of this work, which is also a criterion of RoboCup competitions, is the development of an exploration method for the determination of thermal targets. An algorithm has been developed which relies on giving travel priority to the thermal information emitting targets in the environment. So that the victims can be detected more effectively. Additional methodsg, such as human detection from image processing, detecting carbon dioxide gas, motion detection, etc., can be used to identify the victim, in consideration of the fact that every thermal target in the environment may not be human bein This study only involves detecting thermal targets and directing the mobile robots to them. Successful results are ensured by making the method more stable thanks to tests in both the real environment and the simulation environment. Gazebo is used as the simulation environment, and a differential drive mobile robot with a thermal camera is used for real environment experiments. Since there is no thermal camera in Gazebo simulation environment, a system was designed to represent thermal targets. This system is based on obtaining representative thermal images by applying various filters to normal camera images.

Urban search and rescue robots explore the area which they don't know. They must localize themselves, map the environment, and choose their targets. The usage of robot teams can be very effective for large areas instead of a single robot. Robot teams can be managed with distributed or centric methodologies. In a distributed architecture, each robot should be self-sufficient by means of all search tasks. This also means that each robot needs a rich computational power. Moreover, an optimal exploration strategy requires communication between all the robots. A common way to get such an architecture is applying centric approaches. In centric approaches, each robot can be seen as a mobile sensor with little computational power. They send their measures to the center. The map is generated at the center. Navigation commands are generated at the center according to the exploration strategy. ROS is a very common platform for robotic researchers. It includes several single robot mapping algorithms. But, there is no common mapping algorithm for centric approaches. In this study, we developed a multi-robot version of Hector mapping which is widely used in most robotic researches. For the real-time running ability, we parallelized its optimization procedure. The experimental results shows the effectiveness of our proposed architecture.

Exploration is defined as the selection of target points that yield the biggest contribution to a specific gain function at an initially unknown environment. Exploration for autonomous mobile robots is closely related to mapping, navigation, localization and obstacle avoidance. In this study an autonomous frontier-based exploration strategy is implemented. Frontiers are defined as the border points that are calculated throughout the mapping and navigation stage between known and unknown areas. Frontier-based exploration implementation is compatible with the Robot Operating System (ROS). Also in this study, real robot platform is utilized for testing and the effect of different frontier target assignment approaches are comparatively analyzed by means of total path length and thereby total exploration time.

Curvelet transform (CT) is a multiscale directional transform that enables the use of texture and spatial locality information. In synthetic aperture radar (SAR) imaging, CT is mostly used in speckle noise reduction. This letter utilizes CT for feature extraction in land use classification. Two types of curvelet-based feature extraction methods are implemented for SAR. The first one is defined and used in content-based image retrieval and is based on generalized Gaussian distribution parameter estimation for each curvelet subband. The second implementation is a genuine method that utilizes the use of curvelet subband histograms, namely, histogram of curvelets (HoC). Using the proposed curvelet-based feature extraction method (HoC) on SAR data, better classification accuracies up to 99.56% are achieved compared to original data and H/A/α decomposition features. Compared to speckle-noise-reduced data classification results, it can be said that curvelet-based feature extraction is also robust against speckle noise.