Monocular 3D Localization of Vehicles in Road Scenes

Author(s):  
Haotian Zhang ◽  
Haorui Ji ◽  
Aotian Zheng ◽  
Jenq-Neng Hwang ◽  
Ren-Hung Hwang
Keyword(s):  
Author(s):  
Meiyan Zhang ◽  
Wenyu Cai

Background: Effective 3D-localization in mobile underwater sensor networks is still an active research topic. Due to the sparse characteristic of underwater sensor networks, AUVs (Autonomous Underwater Vehicles) with precise positioning abilities will benefit cooperative localization. It has important significance to study accurate localization methods. Methods: In this paper, a cooperative and distributed 3D-localization algorithm for sparse underwater sensor networks is proposed. The proposed algorithm combines with the advantages of both recursive location estimation of reference nodes and the outstanding self-positioning ability of mobile AUV. Moreover, our design utilizes MMSE (Minimum Mean Squared Error) based recursive location estimation method in 2D horizontal plane projected from 3D region and then revises positions of un-localized sensor nodes through multiple measurements of Time of Arrival (ToA) with mobile AUVs. Results: Simulation results verify that the proposed cooperative 3D-localization scheme can improve performance in terms of localization coverage ratio, average localization error and localization confidence level. Conclusion: The research can improve localization accuracy and coverage ratio for whole underwater sensor networks.


2021 ◽  
Vol 64 (3) ◽  
pp. 117-125
Author(s):  
Rajalakshmi Nandakumar ◽  
Vikram Iyer ◽  
Shyamnath Gollakota

The vision of tracking small IoT devices runs into the reality of localization technologies---today it is difficult to continuously track objects through walls in homes and warehouses on a coin cell battery. Although Wi-Fi and ultra-wideband radios can provide tracking through walls, they do not last more than a month on small coin and button cell batteries because they consume tens of milliwatts of power. We present the first localization system that consumes microwatts of power at a mobile device and can be localized across multiple rooms in settings such as homes and hospitals. To this end, we introduce a multiband backscatter prototype that operates across 900 MHz, 2.4 GHz, and 5 GHz and can extract the backscatter phase information from signals that are below the noise floor. We build subcentimeter-sized prototypes that consume 93 μW and could last five to ten years on button cell batteries. We achieved ranges of up to 60 m away from the AP and accuracies of 2, 12, 50, and 145 cm at 1, 5, 30, and 60 m, respectively. To demonstrate the potential of our design, we deploy it in two real-world scenarios: five homes in a metropolitan area and the surgery wing of a hospital in patient pre-op and post-op rooms as well as storage facilities.


Robotica ◽  
2021 ◽  
pp. 1-18
Author(s):  
Majid Yekkehfallah ◽  
Ming Yang ◽  
Zhiao Cai ◽  
Liang Li ◽  
Chuanxiang Wang

SUMMARY Localization based on visual natural landmarks is one of the state-of-the-art localization methods for automated vehicles that is, however, limited in fast motion and low-texture environments, which can lead to failure. This paper proposes an approach to solve these limitations with an extended Kalman filter (EKF) based on a state estimation algorithm that fuses information from a low-cost MEMS Inertial Measurement Unit and a Time-of-Flight camera. We demonstrate our results in an indoor environment. We show that the proposed approach does not require any global reflective landmark for localization and is fast, accurate, and easy to use with mobile robots.


Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 498
Author(s):  
Chen Zhang ◽  
Kevin Welsher

In this work, we present a 3D single-particle tracking system that can apply tailored sampling patterns to selectively extract photons that yield the most information for particle localization. We demonstrate that off-center sampling at locations predicted by Fisher information utilizes photons most efficiently. When performing localization in a single dimension, optimized off-center sampling patterns gave doubled precision compared to uniform sampling. A ~20% increase in precision compared to uniform sampling can be achieved when a similar off-center pattern is used in 3D localization. Here, we systematically investigated the photon efficiency of different emission patterns in a diffraction-limited system and achieved higher precision than uniform sampling. The ability to maximize information from the limited number of photons demonstrated here is critical for particle tracking applications in biological samples, where photons may be limited.


2021 ◽  
Vol 11 (9) ◽  
pp. 3921
Author(s):  
Paloma Carrasco ◽  
Francisco Cuesta ◽  
Rafael Caballero ◽  
Francisco J. Perez-Grau ◽  
Antidio Viguria

The use of unmanned aerial robots has increased exponentially in recent years, and the relevance of industrial applications in environments with degraded satellite signals is rising. This article presents a solution for the 3D localization of aerial robots in such environments. In order to truly use these versatile platforms for added-value cases in these scenarios, a high level of reliability is required. Hence, the proposed solution is based on a probabilistic approach that makes use of a 3D laser scanner, radio sensors, a previously built map of the environment and input odometry, to obtain pose estimations that are computed onboard the aerial platform. Experimental results show the feasibility of the approach in terms of accuracy, robustness and computational efficiency.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yutaro Shimizu ◽  
Junpei Takagi ◽  
Emi Ito ◽  
Yoko Ito ◽  
Kazuo Ebine ◽  
...  

AbstractThe trans-Golgi network (TGN) has been known as a key platform to sort and transport proteins to their final destinations in post-Golgi membrane trafficking. However, how the TGN sorts proteins with different destinies still remains elusive. Here, we examined 3D localization and 4D dynamics of TGN-localized proteins of Arabidopsis thaliana that are involved in either secretory or vacuolar trafficking from the TGN, by a multicolor high-speed and high-resolution spinning-disk confocal microscopy approach that we developed. We demonstrate that TGN-localized proteins exhibit spatially and temporally distinct distribution. VAMP721 (R-SNARE), AP (adaptor protein complex)−1, and clathrin which are involved in secretory trafficking compose an exclusive subregion, whereas VAMP727 (R-SNARE) and AP-4 involved in vacuolar trafficking compose another subregion on the same TGN. Based on these findings, we propose that the single TGN has at least two subregions, or “zones”, responsible for distinct cargo sorting: the secretory-trafficking zone and the vacuolar-trafficking zone.


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