SLAM technology has recently seen many successes and attracted the attention of high-technological companies. However, how to unify the interface of existing or emerging algorithms, and effectively perform benchmark about the speed, robustness and portability are still problems. In this paper, we propose a novel SLAM platform named GSLAM, which not only provides evaluation functionality, but also supplies useful toolkit for researchers to quickly develop their own SLAM systems. The core contribution of GSLAM is an universal, cross-platform and full open-source SLAM interface for both research and commercial usage, which is aimed to handle interactions with input dataset, SLAM implementation, visualization and applications in an unified framework. Through this platform, users can implement their own functions for better performance with plugin form and further boost the application to practical usage of the SLAM.
Inspired by the ROS2 @cite_38 messaging architecture, GSLAM implements a similar intra-process communication utility class named Messenger. This provides an alternative option to replace ROS inside the SLAM implementation, and maintains the compatibility, that means all ROS defined messages are supported and ROS wrapper are naturally implemented within our framework. Due to the intra-process design, there is no serialization and data transferring, messages are sent without latency and extra cost. Meanwhile the payloads are not limited to ROS defined messages but any copyable data structures. Moreover, we not only provides evaluation functionality, but also supplies useful toolkit for researchers to quickly develop and integrate their own SLAM algorithm.
@cite_38
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This paper studies a new design of a wireless-powered relay network to improve its throughput performance by opportunistic energy harvesting (EH) and information relaying (IR) at the relay node. To enable the relay to implement opportunistic EH and IR, a new protocol, namely, the adaptive harvest-store-forward (AHSF) protocol, is proposed. In the AHSF protocol, the relay is allowed to adaptively switch between an EH mode and a power-splitting (PS)-based IR mode at the beginning of each time frame; moreover, the relay can adaptively determine the amount of energy for IR based on the wireless channel conditions over one finite time horizon, which consists of multiple consecutive time frames. Then, under the proposed protocol, a throughput maximization problem is formulated to optimize the relay operation mode (i.e., EH mode or IR mode) and resource allocation (i.e., time slot, PS ratio, and power allocation) in the IR mode in a finite time horizon. The formulated problem is coupled over time and, thus, is intractable. To address the intractability, dynamic programming is employed to transform the problem into a series of Bellman equations. Based on the Bellman equations, the optimal decision criteria for the relay operation mode is derived, and a time-coupled optimization problem for the resource allocation in the IR mode is addressed by decoupling into two subproblems for two adjacent time frames. By solving the subproblems via convex programming, an optimization policy with causal channel-state information (CSI), which can be implemented online in real time, and an optimization policy with full CSI, which is used to reveal the upper bound of the achieved throughput, are achieved. The simulation results verify that the proposed design can yield significant throughput gains over the existing wireless-powered relaying schemes. Due to the publicly-known deterministic character- istic of pilot tones, pilot-aware attack, by jamming, nulling and spoofing pilot tones, can significantly paralyze the uplink channel training in large-scale MISO-OFDM systems. To solve this, we in this paper develop an independence-checking coding based (ICCB) uplink training architecture for one-ring scattering scenarios allowing for uniform linear arrays (ULA) deployment. Here, we not only insert randomized pilots on subcarriers for channel impulse response (CIR) estimation, but also diversify and encode subcarrier activation patterns (SAPs) to convey those pilots simultaneously. The coded SAPs, though interfered by arbitrary unknown SAPs in wireless environment, are qualified to be reliably identified and decoded into the original pilots by checking the hidden channel independence existing in sub- carriers. Specifically, an independence-checking coding (ICC) theory is formulated to support the encoding decoding process in this architecture. The optimal ICC code is further devel- oped for guaranteeing a well-imposed estimation of CIR while maximizing the code rate. Based on this code, the identification error probability (IEP) is characterized to evaluate the reliability of this architecture. Interestingly, we discover the principle of IEP reduction by exploiting the array spatial correlation, and prove that zero- IEP, i.e., perfect reliability, can be guaranteed under continuously-distributed mean angle of arrival (AoA). Besides this, a novel closed form of IEP expression is derived in discretely-distributed case. Simulation results finally verify the effectiveness of the proposed architecture. The purpose of this project is to investigate solutions for Simultaneous Localization and Mapping (SLAM) in the context of Automated Guided Vehicles (AGVs). This thesis presents implementation details of a prototype system for AGVs, which was developed with the intention of allowing application-specific testing of SLAM. Three of the most prominent open-source SLAM algorithms, available in ROS, have been evaluated and critically compared. Furthermore, basic background and explanation of the critical problems of SLAM are presented. The SLAM algorithms have been evaluated based on resulting map quality as well as resource requirements. Map quality is tested based on both visual comparison with a ground truth and the correctness of estimated distances in the map. In addition to this, results are presented from tests which have been conducted in order to test the SLAMgenerated maps in AGV application areas. This includes tests where critical tasks, such as the robot’s precision while navigating with the use of a SLAM-generated map, has been assessed. The presented prototype system is based on the Robot Operating System (ROS), which includes state-of-the-art libraries and tools for robotic navigation. The prototype enables testing of navigation and mapping software available in ROS by publishing sensor data, from a physical AGV. The implemented software publishes readings from a laser range scanner, wheel encoders and a gyroscope. These sensor reading are published in a standardized way, making them accessible to applications in the ROS framework. The presented results from the tests answers the question of whether or not SLAM is suitable in the intended environment. Energy harvesting (EH) two-hop communications are considered. The transmitter and the relay harvest energy from the environment and use it exclusively for transmitting data. A data arrival process is assumed at the transmitter. At the relay, a finite data buffer is used to store the received data. We consider a realistic scenario in which the EH nodes have only local causal knowledge, i.e., at any time instant, each EH node only knows the current value of its EH process, channel state, and data arrival process. Our goal is to find a power allocation policy to maximize the throughput at the receiver. We show that because the EH nodes have local causal knowledge, the two-hop communication problem can be separated into two point-to-point problems. Consequently, independent power allocation problems are solved at each EH node. To find the power allocation policy, reinforcement learning with linear function approximation is applied. Moreover, to perform function approximation two feature functions which consider the data arrival process are introduced. Numerical results show that the proposed approach has only a small degradation as compared to the offline optimum case. Furthermore, we show that with the use of the proposed feature functions a better performance is achieved compared to standard approximation techniques.