Object Positioning Algorithm Based on Multidimensional Scaling and Optimization for Synthetic Gesture Data Generation

This work studies the feasibility of a novel two-step algorithm for infrastructure and object positioning, using pairwise distances. The proposal is based on the optimization algorithms, Scaling-by-Majorizing-a-Complicated-Function and the Limited-Memory-Broyden-Fletcher-Goldfarb-Shannon. A qualitative evaluation of these algorithms is performed for 3D positioning. As the final stage, smoothing filtering techniques are applied to estimate the trajectory, from the previously obtained positions. This approach can also be used as a synthetic gesture data generator framework. This framework is independent from the hardware and can be used to simulate the estimation of trajectories from noisy distances gathered with a large range of sensors by modifying the noise properties of the initial distances. The framework is validated, using a system of ultrasound transceivers. The results show this framework to be an efficient and simple positioning and filtering approach, accurately reconstructing the real path followed by the mobile object while maintaining low latency. Furthermore, these capabilities can be exploited by using the proposed algorithms for synthetic data generation, as demonstrated in this work, where synthetic ultrasound gesture data are generated.

Integrated Pose Estimation Using 2D Lidar and INS Based on Hybrid Scan Matching

Point cloud data is essential measurement information that has facilitated an extended functionality horizon for urban mobility. While 3D lidar and image-depth sensors are superior in implementing mapping and localization, sense and avoidance, and cognitive exploration in an unknown area, applying 2D lidar is inevitable for systems with limited resources of weight and computational power, for instance, in an aerial mobility system. In this paper, we propose a new pose estimation scheme that reflects the characteristics of extracted feature point information from 2D lidar on the NDT framework for exploiting an improved point cloud registration. In the case of the 2D lidar point cloud, vertices and corners can be viewed as representative feature points. Based on this feature point information, a point-to-point relationship is functionalized and reflected on a voxelized map matching process to deploy more efficient and promising matching performance. In order to present the navigation performance of the mobile object to which the proposed algorithm is applied, the matching result is combined with the inertial navigation through an integration filter. Then, the proposed algorithm was verified through a simulation study using a high-fidelity flight simulator and an indoor experiment. For performance validation, both results were compared and analyzed with the previous techniques. In conclusion, it was demonstrated that improved accuracy and computational efficiency could be achieved through the proposed algorithms.

Design and characterization of a portable ultrasonic indoor 3D positioning system

<div><div><div><p>In this paper, an ultrasonic positioning system is presented and characterized, based on the usage of a portable grid of beacons and of a few fixed anchors. Since the beacon grid can be moved to guarantee line of sight transmissions, the proposed strategy is potentially suitable for accurate positioning of a mobile object in an environment with a complex geometry. The system was tested experimentally, exhibiting a sub-centimeter positioning accuracy in a range up to 4 m.</p></div></div></div>

Design and characterization of a portable ultrasonic indoor 3D positioning system

<div><div><div><p>In this paper, an ultrasonic positioning system is presented and characterized, based on the usage of a portable grid of beacons and of a few fixed anchors. Since the beacon grid can be moved to guarantee line of sight transmissions, the proposed strategy is potentially suitable for accurate positioning of a mobile object in an environment with a complex geometry. The system was tested experimentally, exhibiting a sub-centimeter positioning accuracy in a range up to 4 m.</p></div></div></div>

Logical model of mobile object control

This paper describes a logical model applied as a soft control tool to mobile objects. The model of the logical spatial situation without uncertainty, i.e., according to the law of excluded middle, is considered as the basis. Nonetheless, the motion rules are derived using an approach applied in constructible mathematics and logic. The approach consists in the finitude of variants of control and analyzing all potential traffic scenarios. The constructible object considered in this paper is the situation’s logical model. The constructible approach consists in considering the model of a typical railway station by the example of which the traffic is analyzed. The situation’s logical model is implemented as a condition for potential traffic. This model is described using mathematical logic with the help of logical variables and rules. The control system in this case makes use of permissible versions of logical designs. The control relies on the feasibility of traffic. The system of control rules is developed on the basis of the logical situation’s model and formed without uncertainty. The article provides an analysis of complementary kinds of traffic.