Hybrid Navigation Research Articles

A new hybrid optimization algorithm for multiple mobile robots navigation based on the CS-ANFIS approach

In this article, a novel hybrid navigation technique is discussed for multiple mobile robots in an unknown clustered environment. This new hybrid navigational methodology is based on the cuckoo search algorithm for training the premise part and the least square estimation method for training the consequent parameters of the adaptive neuro-fuzzy inference system. The proposed hybrid optimal path planner is developed based upon a reference motion, direction, distances between the robot and the obstacles, and distances between the robot and the target, to calculate the suitable steering angle. In order to avoid collision against one another, a set of collision prevention rules are embedded into each robot controller, using the Petri Net model. The effectiveness of the algorithm has been demonstrated through a series of simulation experiments. The experimental results are conducted in the laboratory, using a real mobile robot to validate the versatility and effectiveness of the proposed hybrid technique. A comparison of the simulation and experimental results showed, that there is good agreement between them. The results obtained from the proposed hybrid technique are validated by comparison with the results from other intelligent techniques. Finally, it is concluded that the proposed hybrid methodology is efficient and robust in the sense, that it can be implemented in the robot for navigation in any complex terrain.

810 Pseudo Aerodynamic Attitude Calculation and Position Estimation Based on GPSIIMU/ADS Hybrid Navigation by Flight Test

810 Pseudo Aerodynamic Attitude Calculation and Position Estimation Based on GPSIIMU/ADS Hybrid Navigation by Flight Test

Using the delaunay triangulation and voronoi diagrams for navigation in observable environments

The navigation system of mobile robot should have the capability of environment cognition, action decision, motion control, and state monitoring. This paper proposes a prediction algorithm route based on Voronoi diagrams, applicable for mobile robots with range sensors operating in indoor and unknown environments. The proposed control law is a hybrid navigation strategy composed of Voronoi diagrams and Delaunay triangulation, which is used to avoid the routes that may eventually block the advance of the robot. An efficient implementation of the control law is presented. Simulation results validate the efficacy of the proposed modified control law.

칼만 필터를 이용한 이동 로봇의 간이 복합 항법 시스템 설계

칼만 필터를 이용한 이동 로봇의 간이 복합 항법 시스템 설계

HAYABUSA's Optical Hybrid Navigation for Approaching to and Stationkeeping around Asteroid ITOKAWA

HAYABUSA's Optical Hybrid Navigation for Approaching to and Stationkeeping around Asteroid ITOKAWA

회전팔 추진기를 가진 시험용 HAUV의 설계 및 구현

In this paper, we propose the hardware and software of a test-bed of a hovering AUV (autonomous underwater vehicle). Test-bed to develop as the underwater robot for the hovering -type is planning to apply for marine resource development and exploration for deep sea. The RTU that controls a azimuth thruster and a vertical thruster of test-bed is a intergrated-type thruster. The main control unit that collects sensor's data and performs high-speed processing and controls a movement of test-bed is a underwater hybrid navigation system. Also it transfers position, posture, state information of test-bed to the host PC of user using a wireless communication. The host PC checks a test-bed in real time by using a realtime monitoring system that is implemented by LabVIEW.

Microcontroller-based mobile robot positioning and obstacle avoidance

The use of mobile robots is growing in manufacturing facilities, hazardous materials handling, etc. Usually, several sensor systems are used in combination. The task of combining the information into a usable form, suitable for making navigation decisions, is known as sensor fusion. In this paper, the navigation system built on a mobile robot operating in a warehouse is presented focusing on the sensory system used. Hybrid navigation system that combines the perception and dead reckoning is used and gives satisfactory operation. A microcontroller system is designed to control the navigation of a mobile robot while avoiding obstacles. A system of 24 ultrasonic sensors was designed and the operation algorithms were described. The encoder and the ultrasonic sensors used are presented in detail together with the navigation system designed based on their operation.

818 INS/GPS/ADS複合航法システムの開発と飛行試験による評価

818 INS/GPS/ADS複合航法システムの開発と飛行試験による評価

An Intelligent Wheelchair Using Situation Awareness and Obstacle Detection

In this paper, we develop an Intelligent Wheelchair (IW) system for the people with various disabilities. The main function of our system is three-fold: 1) user intention recognition, 2) obstacle detection and avoidance, and 3) situation awareness. For this, it is composed of an electric powered wheelchair, two cameras, 8 ultrasonic sensors, laptop computer and DAQ board. Through analyzing the images obtained from a PC camera, it allows user for controlling the IW using their face movement and mouth shape. In addition to prevent the dangerous situation such as collision with people or traffic vehicles, the hybrid navigation system and situation awareness are simultaneously executed. Using a camera and 8 range sensors, our IW can detect various obstacles and find the safe path to avoid them. In particular, by analyzing the texture properties of the images, it can classify the current situation where a user is standing on as sidewalk, roadway and traffic intersection, which prevents the collisions of vehicle at the traffic intersection. Some participants tested our system and then the results show that it can provide a user friendly, convenient interface and safety wheelchair control.

Total Knee Arthroplasty Using a Hybrid Navigation Technique

The use of computer navigation for primary total knee arthroplasty (TKA) provides the benefits of accurate bone resection, low outlier frequencies, and the restoration of overall mechanical alignment. However, its use also involves the disadvantage of change in technique and workflow that have been associated with steep learning curve and increased surgical time.Furthermore, several investigators have described the potential risks associated with the use of navigation, which include registration errors, notching of the anterior femoral cortex, oversizing of the femoral component, and overresection. [1-4] These risks mean that surgical plans provided by navigation software might require modification intraoperatively, based on the surgeon’s experience and knowledge.On the other hand, conventional TKA has the advantages of familiarity and simplicity. Furthermore, decisions regarding bony resection level are based on measurements taken using a traditional jig and rod, and thus, anterior notching and femoral component oversizing can be avoided. Unfortunately, the conventional technique is more inaccurate and inconsistent in terms of component alignment ability than computer navigation. [5,6]In this article, we describe a hybrid technique that combines the benefits of computer navigation and conventional TKA. This hybrid navigation technique was developed to allow TKA to be performed in-line with accepted conventional TKA practice, but with the accuracy of computer navigation.

A hybrid multi-scale approach for simulation of pedestrian dynamics

One of the most important aspects for a realistic prediction of pedestrian flows is the modelling of human navigation in normal situations such as early design phases of buildings or transportation systems and hubs as well as in evacuation studies to enhance safety in existing infrastructures. To overcome the limitations of current navigation models, this paper proposes a new hybrid multi-scale model, which closely links information between the small-scale and large-scale navigation layer to improve the navigational behaviour. In the presented hybrid navigation model, graph-based methods using visibility graphs are used to model large-scale wayfinding decisions. The pedestrians’ movements between two nodes of the navigation graph are modelled by means of a dynamic navigation field. The navigation field is updated dynamically during the runtime of the simulation, explicitly considering other pedestrians for determining the fastest path.The proposed hybrid approach provides a realistic modelling of human navigational behaviour and thus a realistic prediction of flows since it reflects the human cognitive processes triggered by wayfinding tasks. This includes taking into account other pedestrians for routing decisions who are visible from the current position of the considered pedestrian. The paper discusses the concept and the technical details of the proposed hybrid multi-scale approach in detail and presents an extensive case study demonstrating its advantages.

Fusing Visual Tracking and Navigation for Autonomous Control of An Intelligent Wheelchair

Abstract This paper presents a hybrid navigation and control method for intelligent wheelchair. A robust and semi-supervised vision tracking method using Microsoft Kinect and obstacle avoidance navigation approach are integrated into a two-level control system. Then, position tracking control considering nonholonomic constraints are adopted for the motion control of wheelchairs. An indoor environment is set up for evaluating the application of the proposed approaches. The experimental results show that the proposed method is effective and can be used as a hands-free controller for the intelligent wheelchair.

507 INS/GPS/ADS複合航法装置の飛行実証による性能評価(宇宙工学)

507 INS/GPS/ADS複合航法装置の飛行実証による性能評価(宇宙工学)

A hybrid navigation strategy for multiple mobile robots

A hybrid navigation strategy is proposed in this paper for solving the navigation problem of multiple mobile robots. The proposed strategy integrates three algorithms that represent three different types of existing methods in a layered system. The bottom-up architecture of this system is the main contribution of this paper. This architecture pursues reliable low-level layers that can independently work in as much cases as possible, and the high-level layer is used only when it is necessary for guaranteeing convergence in complex situations. The simulation results show that the proposed strategy has well combined the algorithms of different types from the perspective of pursuing reactivity in the premise of ensuring convergence. Compared with the traditional top-down hybrid architecture, the bottom-up architecture proposed in this paper is more suitable for multi-robot navigation since it can better utilize the advantages of different algorithms to deal with different situations. The experiments on real robots have further verified the applicability of the proposed strategy.

Image navigation as a means to expand the boundaries of fluorescence-guided surgery

Hybrid tracers that are both radioactive and fluorescent help extend the use of fluorescence-guided surgery to deeper structures. Such hybrid tracers facilitate preoperative surgical planning using (3D) scintigraphic images and enable synchronous intraoperative radio- and fluorescence guidance. Nevertheless, we previously found that improved orientation during laparoscopic surgery remains desirable. Here we illustrate how intraoperative navigation based on optical tracking of a fluorescence endoscope may help further improve the accuracy of hybrid surgical guidance. After feeding SPECT/CT images with an optical fiducial as a reference target to the navigation system, optical tracking could be used to position the tip of the fluorescence endoscope relative to the preoperative 3D imaging data. This hybrid navigation approach allowed us to accurately identify marker seeds in a phantom setup. The multispectral nature of the fluorescence endoscope enabled stepwise visualization of the two clinically approved fluorescent dyes, fluorescein and indocyanine green. In addition, the approach was used to navigate toward the prostate in a patient undergoing robot-assisted prostatectomy. Navigation of the tracked fluorescence endoscope toward the target identified on SPECT/CT resulted in real-time gradual visualization of the fluorescent signal in the prostate, thus providing an intraoperative confirmation of the navigation accuracy.

Bridging informal tagging and formal semantics via hybrid navigation

The folksonomies resulting from user-generated tag systems feature rapid adaptability, and reflect the information needs of their supporting user communities. However, they suffer from well-known problems, such as polysemy, heteronymy and lack of recall, which have been addressed in controlled vocabularies and ontologies, which in turn follow slower but more controlled evolution processes. These differences have led to the bridging approach described in this paper, which is based on mapping tags to ontology elements. Mappings can be automatically generated or explicitly provided by user-created assertions between tags and ontology elements. The main objective is to combine existing tag navigation, such as that featured in Delicious, with related tag recommendations obtained from ontology relations, in order to provide a hybrid navigation context that benefits folksonomy browsing. The implementation of such integration, combining Delicious and the OpenCyc knowledge base, is described, along with an evaluation of its potential in improving navigation through the user-generated tag system. The results reveal that the new semantic shortcuts and the decrease in dead ends can substantially influence the collaborative bookmarking experience.

Navigated femoral shaft fracture treatment: Current status

Femoral malrotation is a common complication after internal fixation of a femoral shaft fracture. The only valid, objective monitoring method is computer tomography-assisted torsion measurement between the proximal and distal femur; unfortunately, this can only be carried out postoperatively. A difference of 15° compared to the contralateral femur is seen as an indication for revision. With the development of computer-assisted surgery, new possibilities for performing torsion control and correction intraoperatively has been introduced. These methods also allow for navigation-assisted definition of the optimal incision site, intramedullary access, femoral nail and interlocking. The main problem lies in the extra time of surgery, which is due to performing all the steps of the surgery navigated. The solution for this problem is "hybrid navigation", in which the surgeon can select the steps he needs from the navigation system, depending on his experience or surgical technique.

Autonomous Mobile Robot Navigation by Combining Local and Global Techniques

present article is devoted to develop an algorithm for obstacle avoidance of an autonomous mobile robot based on fuzzy logic/ The method of navigation proposed provides a way of blending the intelligence and optimality of global methods with the reactive dynamic behavior of local ones. This is achieved by using hybrid navigation system composed of two modules, one of which uses the a- priori information and determines roughly the optimal route towards the goal, whereas the other carries out effective navigation decisions using the potential function based local approach. The fuzzy rules are constructed from intuitive and subjective human ways of collision avoidance. The results of the present study are compares favorably with those of well-established algorithms.

A new hybrid navigation algorithm for mobile robots in environments with incomplete knowledge

Focusing on the navigation problem of mobile robots in environments with incomplete knowledge, a new hybrid navigation algorithm is proposed. The novel system architecture in the proposed algorithm is the main contribution of this paper. Unlike most existing hybrid navigation systems whose deliberative layers usually play the dominant role while the reactive layers are only simple executors, a more independent reactive layer that can guarantee convergence without the assistance of a deliberative layer is pursued in the proposed architecture, which brings two benefits. First, the burden of the deliberative layer is released, which is beneficial to guaranteeing real-time property and decreasing resource requirement. Second, some possible layer conflicts in the traditional architecture can be resolved, which improves the system stability. The convergence of the new algorithm has been proved. The simulation results show that compared with three traditional algorithms based on different architectures, the new hybrid navigation algorithm proposed in this paper performs more reliable in terms of escaping from traps, resolving conflicts between layers and decreasing the computational time for avoiding time out of the control cycle. The experiments on a real robot further verify the validity and applicability of the new algorithm.

Novel algorithm for geomagnetic navigation

To solve the highly nonlinear and non-Gaussian recursive state estimation problem in geomagnetic navigation, the unscented particle filter (UPF) was introduced to navigation system. The simulation indicates that geomagnetic navigation using UPF could complete the position estimation with large initial horizontal position errors. However, this navigation system could only provide the position information. To provide all the kinematics states estimation of aircraft, a novel autonomous navigation algorithm, named unscented particle and Kalman hybrid navigation algorithm (UPKHNA), was proposed for geomagnetic navigation. The UPKHNA used the output of UPF and barometric altimeter as position measurement, and employed the Kalman filter to estimate the kinematics states of aircraft. The simulation shows that geomagnetic navigation using UPKHNA could provide all the kinematics states estimation of aircraft continuously, and the horizontal positioning performance is better than that only using the UPF.