Navigation Functions Research Articles

基于扫描上下文和 NDT-ICP 融合方案的果园同步定位与绘图方法研究

Simultaneous localization and mapping (SLAM) is one of the key technologies for agricultural robots to build maps and localize in complex orchard environments and realize unmanned autonomous operations. Due to the complexity of the orchard environment, the single canopy feature and the diffuse reflection of light caused by the leaves, etc., the map construction process of the orchard environment leads to mismatch and increases the cumulative error of the map construction. Aiming at the above problems, this paper propose a navigation map construction method for orchard environment based on the fusion of Scan Context and NDT-ICP. The method firstly searches the Ring key quickly to get the candidate frames, and scores the similarity between the candidate frames and the current frame, and effectively detects the loopbacks by two-stage searching algorithm to reduce the false matches in the map of orchard environment. Meanwhile, a point cloud alignment method based on the fusion of normal distribution transform coarse alignment and iterative nearest point exact alignment is used to reduce the cumulative error of the orchard environment map. The results show that the improved algorithm compensates the drift of the point cloud map with higher mapping accuracy, better real-time performance, lower resource utilization, higher overlap between the trajectory estimation and the real trajectory, smoother loops, and a 4% reduction in CPU occupancy. In the complex orchard environment, the root mean square error and standard deviation of the trajectories of this paper's algorithm are 0.57 m and 0.19 m, which are 68% and 83% higher than those of the loop detection algorithms in the Lightweight Ground Optimized Lidar Trajectory Measurement and Multivariate Terrain Mapping (LeGO-LOAM), respectively. Accurate map construction and low drift pose estimation can be performed.The research algorithm effectively reduces the influence of mis-matching and large cumulative error in the process of map construction in the orchard environment, meets the demand for high-precision environmental mapping in the orchard environment, and provides technical support for promoting unmanned operation in the orchard environment.

Egocentric neural representation of geometric vertex in the retrosplenial cortex

Egocentric neural representations of environmental features, such as edges and vertices, are important for constructing a geometrically detailed egocentric cognitive map for goal-directed navigation and episodic memory. While egocentric neural representations of edges like egocentric boundary/border cells exist, those that selectively represent vertices egocentrically are yet unknown. Here we report that granular retrosplenial cortex (RSC) neurons in male mice generate spatial receptive fields exclusively near the vertices of environmental geometries during free exploration, termed vertex cells. Their spatial receptive fields occurred at a specific orientation and distance relative to the heading direction of mice, indicating egocentric vector coding of vertex. Removing physical boundaries defining the environmental geometry abolished the egocentric vector coding of vertex, and goal-directed navigation strengthened the egocentric vector coding at the goal-located vertex. Our findings suggest that egocentric vector coding of vertex by granular RSC neurons helps construct an egocentric cognitive map that guides goal-directed navigation.

Smart Nursing Wheelchairs: A New Trend in Assisted Care and the Future of Multifunctional Integration.

As a significant technological innovation in the fields of medicine and geriatric care, smart care wheelchairs offer a novel approach to providing high-quality care services and improving the quality of care. The aim of this review article is to examine the development, applications and prospects of smart nursing wheelchairs, with particular emphasis on their assistive nursing functions, multiple-sensor fusion technology, and human-machine interaction interfaces. First, we describe the assistive functions of nursing wheelchairs, including position changing, transferring, bathing, and toileting, which significantly reduce the workload of nursing staff and improve the quality of care. Second, we summarized the existing multiple-sensor fusion technology for smart nursing wheelchairs, including LiDAR, RGB-D, ultrasonic sensors, etc. These technologies give wheelchairs autonomy and safety, better meeting patients' needs. We also discussed the human-machine interaction interfaces of intelligent care wheelchairs, such as voice recognition, touch screens, and remote controls. These interfaces allow users to operate and control the wheelchair more easily, improving usability and maneuverability. Finally, we emphasized the importance of multifunctional-integrated care wheelchairs that integrate assistive care, navigation, and human-machine interaction functions into a comprehensive care solution for users. We are looking forward to the future and assume that smart nursing wheelchairs will play an increasingly important role in medicine and geriatric care. By integrating advanced technologies such as enhanced artificial intelligence, intelligent sensors, and remote monitoring, we expect to further improve patients' quality of care and quality of life.

A novel EMS design framework for SPHTs based on instantaneous layer, driving event layer, and driving cycle layer

To effectively harness the energy-saving potential of series–parallel hybrid transmissions (SPHTs) with multiple gears and modes and to enhance the driving cycle adaptability of the rule-based energy management strategy (RB EMS), this study establishes a novel EMS design framework for SPHTs at three levels: the instantaneous, the driving event, and the driving cycle layers. Firstly, an equivalent fuel factor based on the principles of energy conservation and calorific value measurements is constructed, the energy consumption of different working modes and torque combinations under different instantaneous power units is determined, and the decision conditions of working modes are determined. Secondly, the energy consumption of engine and motor torque combination under constant speed, acceleration and deceleration driving events is compared, and the torque distribution feature of multi-power sources is determined. Thirdly, a driving cycle distribution factor is introduced and calculated using vehicle navigation map information, which can adjust the gear switching condition of parallel driving mode online. Based on above, an RB EMS adjusted with driving cycles (ADC-RB EMS) is proposed. The effectiveness of the proposed strategy is then verified through real-world vehicle tests. The fuel consumption performance of this strategy falls between the RB EMS and the dynamic programming (DP) strategy. According to the fuel consumption results, the RB EMS consumes an additional 0.35 L/100 km of fuel, while the DP strategy saves only 3.66% more energy compared to this strategy. The application potential of driving cycle distribution factor in instantaneous optimal control is tested. Compared with ADC-RB and CD-CS, the fuel saving rate is 1.71% and 5.67% respectively, which proves the energy saving performance of A-ECMS. This study provides a development direction for improving the energy saving effect of the RB EMS.

Addressing the challenges of loop detection in agricultural environments

AbstractWhile visual Simultaneous Localization and Mapping systems are well studied and achieve impressive results in indoor and urban settings, natural, outdoor, and open‐field environments are much less explored and still present relevant research challenges. Visual navigation and local mapping have shown a relatively good performance in open‐field environments. However, globally consistent mapping and long‐term localization still depend on the robustness of loop detection and closure, for which the literature is scarce. In this work, we propose a novel method to pave the way towards robust loop detection in open fields, particularly in agricultural settings, based on local feature search and stereo geometric refinement, with a final stage of relative pose estimation. Our method consistently achieves good loop detections, with a median error of 15 cm. We aim to characterize open fields as a novel environment for loop detection, understanding the limitations and problems that arise when dealing with them. Code is available at: https://github.com/CIFASIS/StereoLoopDetector

Space optical communication system for space optical networks and deep space exploration

The acquisition time of tens to hundreds of seconds in the optical link between satellites makes it difficult to meet the needs of constructing spatial optical networks. In addition, as a basic requirement for deep space explorers, autonomous attitude determination and autonomous navigation demand the installation of separate, expensive, and complex inertial devices, and the communication data rate is too low to meet the timely transmission of large amounts of data. In this paper, we proposed and developed a multifunctional fusion space optical communication system for space optical networks and deep space exploration, which has the functions of autonomous attitude determination, autonomous navigation, and high-speed optical communication. The sub-second acquisition time can meet the requirements of space optical network construction, and the ability of autonomous attitude determination and autonomous navigation significantly reduce the amount of R&D expenses of the explorer; decrease the volume, weight, and power consumption of the explorer; and improve the reliability and autonomous survival ability of the explorer. The paper provides the structure, working principle, and main algorithm models and conducts a feasibility analysis and field experiments. The experimental results showed that the average open-loop pointing accuracy of the optical terminal is 95.8 µrad (attitude determination accuracy), which can be improved to 39.1 µrad after filtering, and the acquisition time is less than 1 s. For deep space exploration, the navigation accuracy is less than 67.6 km in the cruise phase and 10 km in the acquisition phase, and field experiments have also proven its feasibility. The significance of our research work lies in proposing what we believe to be a new system operation scheme and design method for optical communication systems, and its results can be widely applied in all fields of space optical communication.

Identification of Complex Multi-Vessel Encounter Scenarios and Collision Avoidance Decision Modeling for MASSs

Complex multi-vessel encounter situations are a challenging problem for ships to avoid collisions, and the International Regulations for Preventing Collision at Sea, 1972 (COLREGs) do not provide a clear delineation of multi-vessel encounter situations and the responsibility of collision avoidance (CA). Furthermore, Marine Autonomous Surface Ships (MASS), which realize autonomous navigation functions, face the problem of recognizing complex multi-ship encounter situations and the corresponding CA decisions. In this study, we adopt the velocity obstacle (VO) algorithm to visualize and identify the danger of multi-ship encounters with the own ship (OS) as the first viewpoint. Additionally, we consider the motion changes in target ships (TSs) and their possible CA behaviors as the basis of the ship’s CA decision-making. According to COLREGs, a simplified method for classifying the encounter situations of multiple clustered ships is proposed, considering the coupling of collision hazards and CA responsibilities between related TSs. On this basis, the corresponding CA decisions for each classified situation are proposed, and a large number of simulation experiments are conducted based on the proposed method by considering the three-ship and four-ship encounter model in the Imazu problem as an example. The experimental results indicate that the proposed method can effectively recognize the complex multi-ship encounter situation in the Imazu problem, and it can adjust the CA measures of the OS in time according to the COLREGs and the behavior of TSs. This provides the basis and reference for MASS when facing complex multi-ship encounter situations.

Communication Identity of Maize Farmers in the Digital Immigrant Group in Accepting Innovation through the Utilization of Digital Petani Apps

The development of digital technology has brought significant changes in the agricultural sector, including through the peTani Apps digital application that is expected to help farmers. However, adopting this technology is not always easy, especially for farmers in the digital immigrant group. This study aims to identify and examine the process of forming a communication identity of corn farmers in the digital immigrant group who accept innovations through digital peTani Apps. The research method used is descriptive qualitative with a case study approach processed and analyzed using NVivo. The research applied Michael Hecht's Communication Theory of Identity (CTI) in farmers' interaction with new technology. The results showed that farmers' communication identity levels, including personal identity, enactment identity, relational identity, and communal identity, play a significant role in technology adoption. Personal identity resulted in the finding that many farmers felt insecure and inexperienced in using advanced technology, which led to discomfort in using the application. Enactment identity shows that peTani Apps' digital technology innovation has not become part of farmers' daily routine due to difficulties in navigation and understanding functions. Relational identity reveals that community support and social relationships are crucial in adoption. Communal identity reflects resistance to change in communities with strong traditional norms. Overall, the app has not been widely adopted by digital immigrant groups. Social, cultural, and economic factors influence the adoption rate of these technologies, so more targeted strategies and greater support are needed to encourage equitable adoption among farmers.

Research on the Construction Technology of INS Digital Prototype Based on Digital Twin

In response to the continuous advancement of digitalization and intelligence in equipment as mandated by the state, a digital twin-based inertial navigation digital prototype construction scheme has been designed. This scheme supports the realization of intelligent manufacturing, testing, evaluation, and operational assurance throughout the lifecycle of inertial navigation products. This paper decomposes the physical entities of the " three-autonomy " SINS and integrates component-level inertial navigation digital prototypes based on the principles of inertial navigation. The prototypes were integrated using heterogeneous models in simulation software. Pure navigation functionality verification was conducted on the prototypes. The results show that the errors in pure simulation of the inertial navigation digital prototypes constructed in this study are consistent with the physical navigation results of inertial navigation systems, providing a reference for the development of inertial navigation digital twin systems.

Tightly coupled integration of vector HD map, LiDAR, GNSS, and INS for precise vehicle navigation in GNSS-challenging environment

ABSTRACT High-precision positioning and navigation are necessary for autonomous driving. GNSS RTK and INS integrated system is commonly used in vehicular navigation. But it suffers from severe signal reflections and blockages of GNSS signals and error accumulation of INS with MEMS-IMU in GNSS-challenging environment. In addition, high-definition (HD) maps in vector format and light detection and ranging (LiDAR) are two common options for intelligent vehicles. A tightly coupled localization method with vector HD map, LiDAR, GNSS RTK, and INS is proposed to take advantage of their complementary characteristics to accurately navigate a vehicle in a GNSS-challenging environment. The method is based on a particle filter (PF) framework. Lateral positions of particles are constrained by LiDAR measurements and lane information in the vector HD map. A constrained and damped LAMBDA searching method is proposed to update particle weights, aiming to find accurate longitudinal localization. Experimental results prove that our method can maintain sub-meter level horizontal positioning accuracy in GNSS-challenging environment, with improvements of (77%, 75%, 64% and 65%), regarding to three-dimensional position and yaw, compared to traditional GNSS-RTK/INS integration, while the improvement of the popular GNSS-RTK/INS/LiDAR integrated framework LIO-SAM is (16%, 53%, 48% and 51%).

Влияние пола и когнитивного стиля на особенности движений глаз при навигации по карте

<p>We investigated the effects of sex and cognitive style on performance in the map navigation task with various label types (object labels, verbal labels, no labels) in 40 healthy participants (20 men, 20 women, age 24,3±0,8) using eye tracking. The cognitive styles (object, spatial, verbal) were assessed using a questionnaire developed by Blazhenkova and Kozhevnikov [2009]. Only men had a reduced number of fixations during route reproduction compared to route memorization; women had longer saccade durations than men. Participants with spatial cognitive style showed shorter saccade duration compared to object cognitive style. Participants with spatial and verbal cognitive styles had more fixations on maps with verbal labels than on the other maps. Analysis of questionnaire and the number of fixations has demonstrated the link between sex and cognitive style, but the effects of sex and cognitive style are not identical. Sex affects eye movements during the performance of different tasks (map familiarization, route memorization, and route reproduction), while cognitive style determines eye movements during navigation on maps with different types of labels.</p>

Building Community Capital—The Role of Local Area Coordinators in Disability Services: A Critical Review

Local Area Coordination (LAC) roles have been implemented in disability services in many countries, supporting people living with disability to connect with formal and informal support in the community. Embedded in the National Disability Insurance Scheme in Australia, the aspiration is that this LAC role will connect people with disability to supports and enable the generation of greater community capacity and inclusion. Yet, with only a limited evidence base that demonstrates the impact of this approach, a clear measurement framework is needed to provide evidence of the realization of this aspiration. We propose that this impact could be demonstrated by applying a Community Capitals Framework (CCF) as the theoretical base for the LAC role and other community capacity initiatives, such as service navigation within disability reform of disability services. The CCF is premised on seven ‘capitals’—social, natural, cultural, human, political, financial and built that intersect and interact with each other to create positive spirals of change in communities. In this critical literature review, we apply the CCF to map and synthesize existing research on the LAC’s role in building community capital and examine the utility of the CCF as a map for LAC and service navigation practices to enhance community inclusion. For this review, we analyzed peer-reviewed journal papers and grey literature that focused on LAC community capacity building for people with disability in a disability service context published between 2000 and August 2023. Of the 17 publications that met the inclusion criteria, there was no published evidence that comprehensively examined or measured community capacity building consistent with the tenets of the CCF. However, our analysis showed that all capitals, with the exception of natural capital, had been considered, with some indication that investment in these capitals (particularly social capital) could be connected in the positive spiraling way suggested by the CCF. Given the paucity of existing evidence to inform the LAC aspiration for community capacity building, research informed by consumer priorities is needed to inform LAC and service navigation practices to address community needs. The CCF has the potential to develop our understanding of LAC and other community capacity-building initiatives through the measurement of LAC and service navigation services and consumer outcomes, as well as by informing investment to target growth capitals in communities.

Microsurgical anatomy and approaches to thalamic gliomas. Part 1: A cartography guide for navigating to the thalamus. Integrating 3D model rendering with anatomical dissections.

The selection of appropriate microsurgical approaches to treat thalamic pathologies is currently largely subjective. The objective of this study was to provide a structured cartography map for surgical navigation to treat gliomas involving different surfaces of the thalamus. Fifteen formalin-fixed, silicone-injected cadavers (30 sides) were dissected, and 10 adult brain specimens (20 sides) were used to illustrate thalamic microsurgical anatomy using the Klingler fiber dissection technique. Exposures and trajectories for the six most common microsurgical approaches were depicted using MR data from healthy subjects converted into surface-rendered 3D virtual brain models. Additionally, thalamic surfaces exposed with all six approaches were color mapped on the virtual 3D model and compared side-by-side in 360° views with previously reported microsurgical approaches. These 3D models were then used in conjunction with topographic data to guide cadaveric dissection steps. There are two general surgical routes to thalamic lesions: the subarachnoid transcisternal and transcortical routes. The transcisternal route consists of the following three approaches: 1) anterior interhemispheric transcallosal approach, which exposes the anterior and superior thalamus; 2) posterior interhemispheric transcallosal approach, which exposes the posterosuperior thalamus; and 3) supracerebellar infratentorial approach, which exposes the posteromedial cisternal thalamus and can be extended laterally to approach the posterolateral thalamus by cutting the tentorium. The three transcortical approaches are the 1) superior parietal lobule approach, which exposes the posterosuperior thalamus and is particularly advantageous in the setting of hydrocephalus; 2) transtemporal gyrus approach, which exposes the inferolateral thalamus; and 3) transsylvian transinsular approach, which exposes the lateral thalamus (slightly more superiorly and posteriorly) and is advantageous for pathologies extending laterally into the peduncle, lenticular nucleus, or insula. Microsurgical approaches to thalamic gliomas continue to be challenging. Nonetheless, safe and effective cisternal, ventricular, and cortical corridors can be developed with thoughtful planning, anatomical understanding, and knowledge of the advantages, risks, and limitations of each approach. In some cases, it is wise to combine these approaches with staged procedures, as the authors demonstrate in Part 2. In Part 1 of this two-part series, they discuss thalamic microsurgical anatomy and illustrate the trajectory and exposures of all six approaches to guide decision-making. Part 2 discusses their thalamic glioma microsurgical case series, which utilizes these microsurgical approaches.

How do different navigation systems affect emergency response time? A prospective simulation study

ObjectiveThere has not been a theoretical test run in Germany that compares different navigation systems with an industry solution (MapTrip112). The aim of this study was to compare navigation systems...

Augmented Reality Empowered Responsible Tourism: Leveraging Social Media Applications for Generation Z Tourists in the Yogyakarta

This research delves into the integration of augmented reality (AR) technology through Instagram filters to enhance responsible tourism practices. With a specific focus on Generation Z tourists in the Yogyakarta Special District, we recognize the importance of collective action in shaping the future of tourism. Despite the government's continuous efforts, responsible tourism implementation faces challenges, leading to cultural and environmental issues due to the increasing number of tourists. Leveraging the preferences and influence of Generation Z, this study proposes the application of AR through Instagram filters as a solution to engage and educate tourists on responsible tourism principles. The methodology involves the construction of AR system models and Instagram filter user interfaces, followed by observation and interviews with Generation Z users. The results indicate that AR filters can effectively convey information about cultural and historical assets, facilitate digital map navigation, and encourage Generation Z tourists to actively contribute to responsible tourism practices. This research underscores the significance of embracing innovative technologies to foster responsible tourism in the Yogyakarta Special District and emphasizes the collaborative nature of this endeavor, requiring the active participation of the government, tourists, and digital artists for sustainable tourism development.

Distance and grid-like codes support the navigation of abstract social space in the human brain.

People form impressions about others during daily social encounters and infer personality traits from others' behaviors. Such trait inference is thought to rely on two universal dimensions: competence and warmth. These two dimensions can be used to construct a 'social cognitive map' organizing massive information obtained from social encounters efficiently. Originating from spatial cognition, the neural codes supporting the representation and navigation of spatial cognitive maps have been widely studied. Recent studies suggest similar neural mechanism subserves the map-like architecture in social cognition as well. Here we investigated how spatial codes operate beyond the physical environment and support the representation and navigation of social cognitive map. We designed a social value space defined by two dimensions of competence and warmth. Behaviorally, participants were able to navigate to a learned location from random starting locations in this abstract social space. At the neural level, we identified the representation of distance in the precuneus, fusiform gyrus, and middle occipital gyrus. We also found partial evidence of grid-like representation patterns in the medial prefrontal cortex and entorhinal cortex. Moreover, the intensity of grid-like response scaled with the performance of navigating in social space and social avoidance trait scores. Our findings suggest a neurocognitive mechanism by which social information can be organized into a structured representation, namely cognitive map and its relevance to social well-being.

Design of intelligent controller for obstacle avoidance and navigation of electric patrol mobile robot based on PLC

Currently, the obstacle avoidance control of patrol robots based on intelligent vision lacks professional controller module assistance. Therefore, this paper proposes a design method of intelligent controller for obstacle avoidance and navigation of electrical inspection mobile robot based on PLC control. The controller designs a laser range finder to determine the required position of electrical patrol inspection. Use PLC as the core controller, and combine sensors, actuators, communication module and PLC selection module in the process of hardware design to achieve autonomous navigation and obstacle avoidance functions of the robot. Then design the software including the PLC compiler system and the virtual machine module. Based on the above steps, design the control module of obstacle avoidance navigation, which realizes the key link of robot autonomous navigation. The test results show that the controller can successfully avoid obstacles, improve the efficiency and quality of inspection, and achieve accurate and fast obstacle avoidance navigation for the electrical inspection mobile robot.

SLAMuZero: Plan and Learn to Map for Joint SLAM and Navigation

SLAMuZero: Plan and Learn to Map for Joint SLAM and Navigation

Indoor navigation map design based on spatial complexity

ABSTRACT In the face of the complex interior structure of a building, indoor navigation is an important tool for people to arrive at their destination in large public buildings. In this research, we first analyze the complexity of indoor space, which mainly includes spatial entities with rich semantics, but corridors lacking in semantics, poor visibility, and multi-dimensional floors. Then, we designed various indoor navigation maps based on spatial complexity and conducted a comparative analysis between the existing maps and the ones we designed. Participants were recruited to perform three navigation tasks in the study area on-site. The results demonstrate the advantages of using a hierarchical landmark representation for improved spatial knowledge acquisition and the effectiveness of scene-enhanced directional guidance in areas with poor visibility. It is worth noting that the introduction of three-dimensional maps was found to have a positive impact on users’ spatial perception and their ability to sketch routes accurately. In summary, this evidence confirms that maps based on spatial complexity not only enhance navigation efficiency but also have the potential to improve the overall indoor navigation experience.

Review Paper: Key Points on Robot Navigation and Its Practical Uses in the Field of Manufacturing

Key aspects are covered in this review article, along with a brief explanation of mobile robot navigation and its uses in the industrial sector. This study emphasizes the significance of robot navigation in enhancing productivity, efficiency, and safety in manufacturing processes by compiling important ideas from the body of research and literature. This study investigates several robot navigation algorithms and strategies, from simple algorithms to sophisticated ones like SLAM (Simultaneous Localization and Mapping). This study also examines particular issues and concerns about the application of robot navigation systems in industrial settings, such as path planning, obstacle avoidance, and worker cooperation. This paper presents some noted applications of robot navigation, such as material handling, assembly, quality control, and logistics, using case studies and examples. The conversation also touches on new developments and prospective paths for robot navigation technology, highlighting the possibility for more innovation and connection with Industry 4.0 projects. All things considered, this review article is an invaluable tool for scholars, practitioners, and business experts who want to comprehend the function of robot navigation in contemporary manufacturing processes and how it will affect industrial automation in the future.