scholarly journals Variability in Reactions to Instructional Guidance during Smartphone-Based Assisted Navigation of Blind Users

2018 ◽  
Vol 2 (3) ◽  
pp. 1-25 ◽  
Author(s):  
Eshed Ohn-Bar ◽  
João Guerreiro ◽  
Kris Kitani ◽  
Chieko Asakawa
Keyword(s):  
Blind Users ◽  
Assisted Navigation ◽  
Instructional Guidance

Indication and Application of Computer-Assisted Navigation in the HURS Craniofacial Unit: 2 Years’ Experience

2014 ◽  
Vol 75 (S 02) ◽  
Author(s):  
S. Heredero ◽  
J. Solivera ◽  
A. Candau ◽  
A. Dean ◽  
F. Alamillos ◽  
...  
Keyword(s):  
Computer Assisted ◽  
Assisted Navigation

Cervical 1-2 Posterior Instrumented Fusion Utilizing Computer-Assisted Navigation With Harvest of Rib Strut Autograft: 2-Dimensional Operative Video

2021 ◽  
Author(s):  
Timothy J Yee ◽  
Michael J Strong ◽  
Matthew S Willsey ◽  
Mark E Oppenlander
Keyword(s):  
Surface Area ◽  
Odontoid Process ◽  
Odontoid Fracture ◽  
Patient Specific ◽  
Computer Assisted ◽  
Type Ii ◽  
Instrumented Fusion ◽  
Assisted Navigation ◽  
Patient Consent ◽  
Posterior Instrumented Fusion

Abstract Nonunion of a type II odontoid fracture after the placement of an anterior odontoid screw can occur despite careful patient selection. Countervailing factors to successful fusion include the vascular watershed zone between the odontoid process and body of C2 as well as the relatively low surface area available for fusion. Patient-specific factors include osteoporosis, advanced age, and poor fracture fragment apposition. Cervical 1-2 posterior instrumented fusion is indicated for symptomatic nonunion. The technique leverages the larger posterolateral surface area for fusion and does not rely on bony growth in a watershed zone. Although loss of up to half of cervical rotation is expected after C1-2 arthrodesis, this may be better tolerated in the elderly, who may have lower physical demands than younger patients. In this video, we discuss the case of a 75-yr-old woman presenting with intractable mechanical cervicalgia 7 mo after sustaining a type II odontoid fracture and undergoing anterior odontoid screw placement at an outside institution. Cervical radiography and computed tomography exhibited haloing around the screw and nonunion across the fracture. We demonstrate C1-2 posterior instrumented fusion with Goel-Harms technique (C1 lateral mass and C2 pedicle screws), utilizing computer-assisted navigation, and modified Sonntag technique with rib strut autograft.  Posterior C1-2-instrumented fusion with rib strut autograft is an essential technique in the spine surgeon's armamentarium for the management of C1-2 instability, which can be a sequela of type II dens fracture. Detailed video demonstration has not been published to date.  Appropriate patient consent was obtained.

scholarly journals Smartphone-Based Inertial Odometry for Blind Walkers

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4033
Author(s):  
Peng Ren ◽  
Fatemeh Elyasi ◽  
Roberto Manduchi
Keyword(s):  
Particle Filtering ◽  
Inertial Sensors ◽  
State Of The Art ◽  
Inertial Sensor ◽  
Mean Shift ◽  
Gait Pattern ◽  
Comparative Assessment ◽  
Pedestrian Tracking ◽  
Step Counter ◽  
Assisted Navigation

Pedestrian tracking systems implemented in regular smartphones may provide a convenient mechanism for wayfinding and backtracking for people who are blind. However, virtually all existing studies only considered sighted participants, whose gait pattern may be different from that of blind walkers using a long cane or a dog guide. In this contribution, we present a comparative assessment of several algorithms using inertial sensors for pedestrian tracking, as applied to data from WeAllWalk, the only published inertial sensor dataset collected indoors from blind walkers. We consider two situations of interest. In the first situation, a map of the building is not available, in which case we assume that users walk in a network of corridors intersecting at 45° or 90°. We propose a new two-stage turn detector that, combined with an LSTM-based step counter, can robustly reconstruct the path traversed. We compare this with RoNIN, a state-of-the-art algorithm based on deep learning. In the second situation, a map is available, which provides a strong prior on the possible trajectories. For these situations, we experiment with particle filtering, with an additional clustering stage based on mean shift. Our results highlight the importance of training and testing inertial odometry systems for assisted navigation with data from blind walkers.

Research on outdoor AGV precise navigation based on BDS/INS data fusion

2021 ◽  
pp. 1-12
Author(s):  
Yongwei Tang ◽  
Huijuan Hao ◽  
Jun Zhou ◽  
Yuexiang Lin ◽  
Zhenzhen Dong
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Navigation System ◽  
Integrated Navigation ◽  
Complex Environments ◽  
Assisted Navigation ◽  
Precise Control ◽  
Bee Colony ◽  
Navigation Algorithm ◽  
Navigation Error

AGV (Automated Guided Vehicle) technology has attracted increasing attention. Precise control of AGV position and attitude information in complex operating environment is a key part of smart factories. With outdoor AGV as a platform, this study uses BDS/INS combined navigation system combining Beidou positioning system and inertial navigation system and takes the velocity and position difference between BDS and INS as a model. An integrated navigation method is proposed to improve bee colony algorithm and optimize the BP neural network-assisted Kalman filtering to achieve accurate positioning. Moreover, the optimization of BP neural network navigation using INS navigation, network-assisted navigation and bee colony algorithm is simulated. Results demonstrate that the integrated navigation algorithm has effectiveness and feasibility, and can solve the problems of BDS misalignment and large INS navigation error in complex environments.

scholarly journals Development and Experimental Evaluation of a Low-Cost Cooperative UAV Localization Network Prototype

2018 ◽  
Vol 7 (4) ◽  
pp. 42 ◽  
Author(s):  
Salil Goel ◽  
Allison Kealy ◽  
Bharat Lohani
Keyword(s):  
Information Sharing ◽  
Inertial Sensors ◽  
Low Cost ◽  
Wide Band ◽  
Cooperative Networks ◽  
Global Navigation Satellite Systems ◽  
Cooperative Localization ◽  
Cooperative Network ◽  
Precise Positioning ◽  
Assisted Navigation

Precise localization is one of the key requirements in the deployment of UAVs (Unmanned Aerial Vehicles) for any application including precision mapping, surveillance, assisted navigation, search and rescue. The need for precise positioning is even more relevant with the increasing automation in UAVs and growing interest in commercial UAV applications such as transport and delivery. In the near future, the airspace is expected to be occupied with a large number of unmanned as well as manned aircraft, a majority of which are expected to be operating autonomously. This paper develops a new cooperative localization prototype that utilizes information sharing among UAVs and static anchor nodes for precise positioning of the UAVs. The UAVs are retrofitted with low-cost sensors including a camera, GPS receiver, UWB (Ultra Wide Band) radio and low-cost inertial sensors. The performance of the low-cost prototype is evaluated in real-world conditions in partially and obscured GNSS (Global Navigation Satellite Systems) environments. The performance is analyzed for both centralized and distributed cooperative network designs. It is demonstrated that the developed system is capable of achieving navigation grade (2–4 m) accuracy in partially GNSS denied environments, provided a consistent communication in the cooperative network is available. Furthermore, this paper provides experimental validation that information sharing is beneficial to improve positioning performance even in ideal GNSS environments. The experiments demonstrate that the major challenges for low-cost cooperative networks are consistent connectivity among UAV platforms and sensor synchronization.

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