Navigation Functions Research Articles

MASS and COLREGS–Adaptability, Challenges and Coping Strategies

Discussions surrounding Maritime Autonomous Surface Ships (MASS) are occurring in academia, industry, and the International Maritime Organization (IMO). Automatic collision avoidance, as one of the key technologies of MASS, is the core of the autonomous navigation function of MASS, and its role is to solve the autonomous collision avoidance problem during MASS navigation. Convention on the International Regulations for Preventing Collisions at Sea (COLREGS) is a fundamental basis for automatic collision avoidance, and the navigation of MASS should adhere to it. However, the applicability of MASS to COLREGS has not yet been resolved. Responding to these issues, the paper proceeds to analyze the principal challenges of MASS to COLREGS in terms of the application of MASS to good seamanship, the neglect provision, the lookout provision, the insight of one another provision, and the problems of the deviation provision. Furthermore, suggestions are put forth for the revision of COLREGS, including the mode of revision, the reconstruction of MASS collision liability, the long-term coexistence of MASS and traditional ships, and the risk control of COLREGS revision in the context of artificial intelligence. These suggestions aim to establish a foundation for a more effective adaptation to the advent of the MASS era.

High-Resolution Collaborative Forward-Looking Imaging Using Distributed MIMO Arrays

Airborne radar forward-looking imaging holds significant promise for applications such as autonomous navigation, battlefield reconnaissance, and terrain mapping. However, traditional methods are hindered by complex system design, azimuth ambiguity, and low resolution. This paper introduces a distributed array collaborative, forward-looking imaging approach, where multiple aircraft with linear arrays fly in parallel to achieve coherent imaging. We analyze signal model characteristics and highlight the limitations of conventional algorithms. To address these issues, we propose a high-resolution imaging algorithm that combines an enhanced missing-data iterative adaptive approach with aperture interpolation technique (MIAA-AIT) for effective signal recovery in distributed arrays. Additionally, a novel reference range cell migration correction (reference RCMC) is employed for precise range–azimuth decoupling. The forward-looking algorithm effectively transforms distributed arrays into a virtual long-aperture array, enabling high-resolution, high signal-to-noise ratio imaging with a single snapshot. Simulations and real data tests demonstrate that our method not only improves resolution but also offers flexible array configurations and robust performance in practical applications.

An Automatic Mapping Method of Navigation Map for Outdoor Road Scenes

Abstract. In the process of autonomous navigation of outdoor mobile robots, four modules are involved: perception, localization, planning, and controlling. The perception module utilizes sensors such as cameras and radars based on various principles to analyze the robot's surroundings in real-time. The localization module uses GPS (Global Positioning System), IMU (Inertial Measurement Unit), and prior maps for real-time positioning analysis. The planning module plans optimal path based on the outputs of the first two modules, and the controlling module directs the robot's chassis to move along the planned optimal path. For the localization module, the accuracy of GPS positioning results heavily depends on weather conditions and GPS signal receptions. Even if the positioning results of imu are integrated, the positioning accuracy still cannot meet the needs of robot navigation. Therefore, using prior maps for repositioning can compensate for this accuracy deficiency. The planning module also requires path planning based on prior maps. If the a priori map storage is large, it will lead to difficulties in usage, maintenance, and updates. Therefore, it is crucial to research lightweight navigation map mapping methods. In this paper, an automatically mapping method of lightweight navigation maps is proposed, combining cameras and LiDAR (Light Detection and Ranging), including semantic informations necessary for outdoor navigation positioning, such as pole-like objects and traffic signs for robot longitudinal positioning, and lane line elements for robot lateral positioning. This method automatic generates robot navigation maps in Lanelet2 format, providing support for subsequent positioning and path planning modules.

SURGICAL TREATMENT OF RECTAL CANCER WITH PRESERVATION OF THE LEFT COLIC ARTERY AND ICG NAVIGATION

Goal. To analyze the peculiarities of surgical diagnosis of lymphogenic metastasis in patients with colorectal cancer. Generalization of data from Ukrainian and foreign literature, results of randomized studies and meta-analyses. The study is based on the results of observation of 88 patients with colorectal cancer (CRC) of the prospective study group. To analyze the features of surgical diagnostics of lymphogenic metastasis in patients with colorectal cancer. Materials and methods. The results of surgical treatment of 88 patients with rectal cancer were analyzed and systematized. These patients underwent examination and treatment in 2023-2024 at the "Prykarpattian Clinical Oncology Center of the Ivano-Frankivsk Regional Council." The study included patients with stage II-III colorectal cancer (T2-3N0-2M0) without complicated courses. All patients received treatment based on NCCN recommendations. Surgical treatment was performed in standard volume with the removal of all regional lymph node groups and preservation of the left colic artery using real-time lymph node mapping with indocyanine green. All patients were divided into two study groups: Group I included 45 patients who underwent anterior or low anterior resection of the rectum with preservation of the left colic artery. This group was subdivided into two subgroups: Ia – 13 patients who underwent intraoperative indocyanine green injection for real-time lymph node visualization. Ib – 32 patients who did not receive this drug but underwent the same volume of surgery. Group II consisted of 43 patients who underwent anterior or low anterior resection of the rectum with high ligation of the inferior mesenteric artery. This group served as the control group. Results. The main mechanisms of lymphogenic metastasis in colorectal cancer patients in Ivano-Frankivsk were characterized. Literature data on the features of surgical diagnostics of colorectal cancer metastasis were summarized. A review of literature shows the social significance of these studies, as this pathology often leads to patient disability, requiring surgical interventions and further palliative treatment due to the widespread metastasis associated with this disease. The priority task for researchers remains the search for the most effective treatment methods for this pathology, based on randomized studies of colorectal cancer treatment and international protocols. According to the literature, surgical treatment of colorectal cancer remains insufficiently effective at the current stage of oncology. Modern methods offer low 5-year survival rates, emphasizing the need to study factors for individualized treatment. The overall 5-year survival rate for colorectal cancer patients from 2018-2022 was (45.8±2.3)%. The effectiveness of using real-time ICG navigation for lymph node mapping and preservation of the left colic artery in stage II-III (T2-4N1-2M0) rectal cancer patients has been proven. This technique allows for optimal lymphadenectomy, reducing the frequency of surgical complications by 14.7% (p<0.05). Conclusion. Ensuring radical resection of rectal cancer while maximizing blood supply preservation to the anastomosis is the main goal of colorectal surgeons. Over the past two decades, surgical techniques have significantly improved due to advancements in surgical equipment. It is anticipated that surgical technologies will further evolve towards enhancement and individualization in the future. Our procedure serves as an example of modern and personalized rectal cancer surgery.

Map Construction and Positioning Method for LiDAR SLAM-Based Navigation of an Agricultural Field Inspection Robot

In agricultural field inspection robots, constructing accurate environmental maps and achieving precise localization are essential for effective Light Detection And Ranging (LiDAR) Simultaneous Localization And Mapping (SLAM) navigation. However, navigating in occluded environments, such as mapping distortion and substantial cumulative errors, presents challenges. Although current filter-based algorithms and graph optimization-based algorithms are exceptionally outstanding, they exhibit a high degree of complexity. This paper aims to investigate precise mapping and localization methods for robots, facilitating accurate LiDAR SLAM navigation in agricultural environments characterized by occlusions. Initially, a LiDAR SLAM point cloud mapping scheme is proposed based on the LiDAR Odometry And Mapping (LOAM) framework, tailored to the operational requirements of the robot. Then, the GNU Image Manipulation Program (GIMP) is employed for map optimization. This approach simplifies the map optimization process for autonomous navigation systems and aids in converting the Costmap. Finally, the Adaptive Monte Carlo Localization (AMCL) method is implemented for the robot’s positioning, using sensor data from the robot. Experimental results highlight that during outdoor navigation tests, when the robot operates at a speed of 1.6 m/s, the average error between the mapped values and actual measurements is 0.205 m. The results demonstrate that our method effectively prevents navigation mapping distortion and facilitates reliable robot positioning in experimental settings.

Computed tomography and structured light imaging guided orthopedic navigation puncture system: effective reduction of intraoperative image drift and mismatch.

Image-guided surgical navigation systems are widely regarded as the benchmark for computer-assisted surgical robotic platforms, yet a persistent challenge remains in addressing intraoperative image drift and mismatch. It can significantly impact the accuracy and precision of surgical procedures. Therefore, further research and development are necessary to mitigate this issue and enhance the overall performance of these advanced surgical platforms. The primary objective is to improve the precision of image guided puncture navigation systems by developing a computed tomography (CT) and structured light imaging (SLI) based navigation system. Furthermore, we also aim to quantifying and visualize intraoperative image drift and mismatch in real time and provide feedback to surgeons, ensuring that surgical procedures are executed with accuracy and reliability. A CT-SLI guided orthopedic navigation puncture system was developed. Polymer bandages are employed to pressurize, plasticize, immobilize and toughen the surface of a specimen for surgical operations. Preoperative CT images of the specimen are acquired, a 3D navigation map is reconstructed and a puncture path planned accordingly. During surgery, an SLI module captures and reconstructs the 3D surfaces of both the specimen and a guiding tube for the puncture needle. The SLI reconstructed 3D surface of the specimen is matched to the CT navigation map via two-step point cloud registrations, while the SLI reconstructed 3D surface of the guiding tube is fitted by a cylindrical model, which is in turn aligned with the planned puncture path. The proposed system has been tested and evaluated using 20 formalin-soaked lower limb cadaver specimens preserved at a local hospital. The proposed method achieved image registration RMS errors of 0.576 ± 0.146 mm and 0.407 ± 0.234 mm between preoperative CT and intraoperative SLI surface models and between preoperative and postoperative CT surface models. In addition, preoperative and postoperative specimen surface and skeletal drifts were 0.033 ± 0.272 mm and 0.235 ± 0.197 mm respectively. The results indicate that the proposed method is effective in reducing intraoperative image drift and mismatch. The system also visualizes intraoperative image drift and mismatch, and provides real time visual feedback to surgeons.

The Share of Data in Maritime Communications is Increasing

Communication is of great importance for the safe and delay-free navigation of ships. Especially life/property safety, navigational warnings, weather forecast reports, storm warnings, navigation maps, etc. Timely transmission of information to ships is only possible with effective maritime communications. In addition, communication is of great importance in making appropriate navigation plans based on the information received from the ships. In recent years, the share of data communication in individual and corporate communications has been increasing. In order to benefit from the great conveniences and opportunities provided by data communication in maritime communication systems, very radical decisions have recently been taken within IMO. These regulations made at the international level paved the way for data communication in close-range maritime communication systems. In line with these regulations, broadband data communication between the ship and the land will begin to be made via VHF devices in the next few years. Another development that will improve broadband data communication in maritime communication systems has been in Near Orbit Satellite systems. The technical features of these systems, the number of which has been increasing in recent years, are extremely suitable for data communication between ship and land. Among these, the Starlink system completes its network in space faster than other satellite systems. It is inevitable that the Starlink system, whose global satellite structure will be completed to a large extent by the end of 2025, will be used to a large extent in data communication between ships and land and between ships with each other. With the use of broadband data feature in the near future, it will be possible for ships to navigate much more safely, efficiently and with a reduced risk of accidents. For this purpose, maritime enterprises, ship personnel and land units must be informed about these developments and their communication infrastructure must be established by taking these systems into consideration.

LIDAR adaptive parameters selection and target pointing control for close-proximity space operations

This paper deals with advanced Guidance, Navigation and Control (GNC) functions required to enable autonomous and safe operations of a chaser spacecraft in close-proximity to an uncooperative space target, as in Active Debris Removal or On-Orbit servicing scenarios. Specifically, it presents an original approach to autonomously and adaptively select the field of view and resolution of a scanning LIDAR to improve both state estimation accuracy and computational efficiency of a LIDAR-based relative navigation system. In general, the correct operation of such system is also determined by the capability to keep the boresight axis of the relative navigation sensor aligned with the target geometric center. To address this task, an original control technique, based on the sliding-mode formulation and relying on a reduced attitude representation, is proposed. This control scheme is also compared to state-of-the-art PD and PID approaches in terms of pointing accuracy and control effort. The proposed techniques have been numerically validated in a simulation environment integrating the chaser attitude control and the LIDAR-based relative navigation functions in a closed-loop architecture. The simulation environment realistically reproduces the generation of LIDAR-based point clouds, and the spacecraft relative dynamics in close proximity. Results show that the adaptive selection of the LIDAR operational parameters improves the relative navigation performance, while the proposed sliding-mode control guarantees higher pointing accuracy than PD and PID control approaches.

Fault Tolerant Metric Dimension of Arithmetic Graphs

For a graph G , two vertices x , y ∈ G are said to be resolved by a vertex s ∈ G , if d ( x | s ) ≠ d ( y | s ) . The minimum cardinality of such a resolving set R in G is called its metric dimension. A resolving set R is said to be fault-tolerant, if for every p ∈ R , R − p preserves the property of being a resolving set. A fault-tolerant metric dimension of G is a minimal possible order fault-tolerant resolving set. A wide variety of situations, in which connection, distance, and connectivity are important aspects, call for the utilisation of metric dimension. The structure and dynamics of complex networks, as well as difficulties connected to robotics network design, navigation, optimisation, and facility positioning, are easier to comprehend as a result of this. As a result of the relevant concept of metric dimension, robots are able to optimise their methods of localization and navigation by making use of a limited number of reference locations. As a consequence of this, numerous applications of robotics, including collaborative robotics, autonomous navigation, and environment mapping, have become more precise, efficient, and resilient. The arithmetic graph A l is defined as the graph with its vertex set as the set of all divisors of l , where l is a composite number and l = p γ 1 1 p η 2 2 , … , p n n , where p n ≥ 2 and the p i ’s are distinct primes. Two distinct divisors x , y of l are said to have the same parity if they have the same prime factors (i.e., x = p 1 p 2 and y = p 2 1 p 3 2 have the same parity). Further, two distinct vertices x , y ∈ A l are adjacent if and only if they have different parity and gcd ( x , y ) = p i (greatest common divisor) for some i ∈ { 1 , 2 , … , t } . This article is dedicated to the investigation of the arithmetic graph of a composite number l , which will be referred to throughout the text as A l . In this study, we compute the fault-tolerant resolving set and the fault-tolerant metric dimension of the arithmetic graph A l , where l is a composite number.

An improved SLAM algorithm for substation inspection robot based on the fusion of IMU and visual information

In the past, manual inspection was often used for equipment inspection in indoor environments such as substation rooms and chemical plant rooms. This way often accompanies high labor intensity, low inspection efficiency, and low safety, which is difficult to meet the increasingly stringent requirements of indoor equipment operation and maintenance management. For dealing with these issues, a VIORB-SLAM2 algorithm based on the integration of IMU and visual information, was proposed by this paper. Firstly, the IMU data and image data were integrated to restore scale information of cameras, and then an error function was established to enhance the algorithm’s robustness. Secondly, in order to improve the accuracy of the algorithm, the random sampling consensus method was used to eliminate the wrong matching points in feature point matching, and the normalized cross-correlation matching was employed to constrain key frame matching conditions. Finally, through the iterative closest point method to stitch the point clouds, a dense map for navigation was constructed. The experimental results show that the algorithm designed by this paper has solved the shortcomings of applying the ORB-SLAM2 algorithm to indoor inspection robots while achieving high positioning accuracy, which can be combined with other algorithms in the field of artificial intelligence for object detection and semantic map construction in the future.

Abstract C073: Enhancing cancer care: Insights from the CAFÉ Trial on Financial Navigation and program improvements

Abstract Purpose: Cancer-related financial hardship is prevalent and associated with poor health outcomes. CAFÉ is a multi-site randomized control trial (RCT) testing a financial navigation intervention to reduce financial hardship for people newly diagnosed with cancer. Methods: The CAFÉ trial randomized participants to usual care or one of two intervention arms. Participants randomized to the intervention arms received either brief (one proactive outreach) or extended (three proactive outreaches) contact from a navigator to assess for financial concerns. Navigation services lasted for 6 months. At the final outreach call, we asked participants to provide feedback on areas of program improvement. We also conducted two rounds of interviews (early and later intervention) with the CAFÉ financial navigators to explore lessons learned regarding implementing the program. Data was summarized using a content analysis approach. Results: Among 201 participants (102 extended; 99 brief) that offered feedback at the final outreach call, 64% (129) were satisfied with the navigation program and did not feel changes were warranted. Suggested improvements included: improving the timeliness and usefulness of resources offered (18%; 37); offering earlier and more frequent/ongoing outreach from the navigators (14%; 28); receiving more active support from the navigators in accessing or processing information and resources (13%; 27); and increasing the scope of the navigator role to aid in complicated billing or insurance questions (9%; 19). Improving timeliness/usefulness of resources offered and frequency of outreach was noted slightly more often by participants in the brief arm (36%) than those in the extended arm (29%). Financial navigators (n=4) reported parallel themes for improvement including: expanding the navigator’s scope to help with billing, insurance, and cost questions; tailoring resources offered to the participant’s specific needs; and reaching out to participants closer to their cancer diagnosis. Navigators identified additional improvements including: having sufficient staffing and time to fulfill navigator functions; creating a simple and integrated documentation/tracking tool within the organization’s electronic health record; and translating important resources and instructions, like financial assistance applications, into Spanish. Conclusion: The overall satisfaction with the CAFÉ program underscores its potential to positively impact the well-being of individuals newly diagnosed with cancer. However, patients and navigators alike underscored important areas of improvement that health care systems may want to consider for future implementation: timeliness and length of the outreach, personalization of offered resources, and expansion of navigator role. Navigators also noted opportunities for improving data tracking and staffing. Future analyses will determine the effectiveness of the CAFÉ program on financial, health and healthcare outcomes. Citation Format: Jennifer L. Schneider, Blake Locher, Jennifer S. Rivelli, Deborah A. King, Lisa Shulman, Amanda F. Petrik, Nora B. Henrikson, Matthew P. Banegas. Enhancing cancer care: Insights from the CAFÉ Trial on Financial Navigation and program improvements [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C073.

Replay shapes abstract cognitive maps for efficient social navigation

Replay shapes abstract cognitive maps for efficient social navigation

Multi-Robot Path Planning Algorithm for Collaborative Mapping under Communication Constraints

In extensive outdoor collaborative exploration tasks, multiple robots require efficient path planning methods to ensure rapid and comprehensive map construction. However, current collaborative mapping algorithms often integrate poorly with path planning, especially under limited communication conditions. Such conditions can complicate data exchange, leading to inefficiencies and missed areas in real-world environments. This paper introduces a path planning approach specifically designed for distributed collaborative mapping tasks, aimed at enhancing map completeness, mapping efficiency, and communication robustness under communication constraints. We frame the entire task as a k-Chinese Postman Problem (k-CPP) and optimize it using a genetic algorithm (GA). This method fully leverages topology maps to efficiently plan subpaths for multiple robots, ensuring thorough coverage of the mapping area without the need for prior navigation maps. Additionally, we incorporate communication constraints into our path planning to ensure stable data exchange among robots in environments with only short-range communication capabilities. Field experiment results highlight the superior performance of our method in terms of stability, efficiency, and robust inter-robot communication.

Эргонимический миф Гермеса: к исследованиям религиозной жизни юридических лиц

The article is devoted to the latest forms of manifestation of religiosity in the city space. The study focuses on studying the micro-levels of religious life in urban ergonymy. By examining store signs, navigation maps, and goods on the shelves of chain stores using the names of the gods of Ancient Greece, the article sets the task of reconstructing a non-verbalized mythological narrative composed by ergonyms and product names. The religious life of urban space is understood as the practices of piety characteristic of ancient Greek religiosity: invocation and dedication. The specific mechanisms of cultural reproduction in Ancient Greece and Europe of the 21st century are reconstructed. Based on the distinction made, the myth-socializing function of modern education in the process of broadcasting the mythological narrative and reinterpreting the Olympic myth is described. The article refers to data on the religious life of legal entities. Based on an analysis of the frequency of mentioning the names of the Olympic gods in the unified register of legal entities, and a comparison of the names of the gods with the declared forms of economic activity, the Olympic myth of the 21st century — the “Ergonymic Myth of Hermes” — is reconstructed. The article assumes scaling up the research to the study of “chorographies” — materially embodied spaces of the sacred on the streets of modern cities. The study of chorographies is proposed as a new methodology for studying culture and human coexistence.

Method of Motion Planning for Digital Twin Navigation and Cutting of Shearer.

To further enhance the intelligence level of coal mining faces and achieve the autonomous derivation, learning, and optimization of shearer navigation cutting, this paper proposes the methods of shearer digital twin navigation cutting motion planning based on the concept of shearer autonomous navigation cutting technology and intelligent coal mining face digital twins. This study includes the digital twin theory and the construction method of the shearer digital twin navigation cutting motion planning system based on this theory. Based on the digital twin theory, a shearer digital twin navigation cutting motion planning system was constructed. This system supports the service functions of the shearer cutting digital twin, dynamic navigation map digital twin, reinforcement learning environment construction, and motion planning through the physical perception layer, comprehensive data layer, and digital-model fusion analysis layer. Finally, by comparing the effects of the DQN-NAF and DDPG deep reinforcement learning algorithms in the shearer motion planning task within the constructed digital twin environment, the results show that the DQN-NAF algorithm demonstrates better performance and stability in solving the shearer digital twin motion planning task.

Empowerment of Augmented Reality (AR) for Patient Education and Engagement: Medication Adherence Programs' Impact on Public Health Outcomes

The entire effectiveness of pharmacological treatment depends on patients taking their medications as prescribed. Patient education is a vital component of the endeavours to enhance adherence to medications. However, many people still fail to take their prescription pills as prescribed. In addition to having access to healthcare, those who follow their doctors' orders greatly improve their chances of a positive outcome. The unfortunate reality is that many people do not take their medications as prescribed, which has led to deteriorating health, higher healthcare costs, and more overall costs. Hence, this paper presents the Smart Augmented Reality-based Patient Medication Adherence Program (SAR-PMAP) model for effective patient education and engaging medication. The augmented reality spectacles help those with trouble keeping track of their medication, and the model encourages patients to take their prescriptions as prescribed. Users may easily go to their homes with the aid of the navigation functions, and patients with impaired eyesight can benefit from the audio option that gives out the date and time. Given all this data, the Medication Coach Intelligent Agent (MCIA) takes the lead in making comprehensive decisions so patients can get autonomous, individualized, and unobtrusive treatments.

A web-based travel package management system integrated with QR code

The tourism industry is associated with people travelling either domestically or abroad, for business, social, or recreational reasons. This industry integrates numerous services and activities such as tourism organization, marketing, hotel industry, transportation services, food and beverage activities, retail stores and various other activities under one umbrella. In addition to generating income and jobs, tourism is the best way to promote the nation's image. As the economy and living conditions have improved, so too has the tourist sector, and more people are turning to vacations as a way to alleviate stress and unwind. Currently, travel agencies handle a lot of data with low efficiency and a lot of mistakes. Therefore, this study developed a comprehensive integration of QR code for package travel management system that caters to users in Malaysia, offering functionalities such as itinerary customization, QR code generation and access to essential travel information. The development of this project adopts the Waterfall Methodology, encompassing phases such as planning, requirement analysis, design, implementation and testing. The application is crafted using the Visual Studio Code. The study conducted a User Acceptance Testing (UAT) using questionnaires to evaluate the system's effectiveness and user-friendliness to thirty respondents including family members of frequent travellers and randomly selected community members. Positive feedbacks with Perceived Ease of Use (PEU) scoring 3.6, Attitude of Using (ATT) at 3.7, Perceived Usefulness (PU) scoring 3.4, and Intention to Use (IU) obtaining 3.9, were gathered from the analysis and findings that emphasizing the QR code system's potential as a cost-effective and efficient solution for travellers to monitor and optimize their travel experiences. Future work involves adding maps for easy navigation and implementing augmented reality (AR) for virtual destination previews.

Brain–computer interface for simultaneous dual‐region spatial coding in hippocampal and somatosensory cortex of freely behaving rats

AbstractDecoding of spatial information from place cells is currently limited to individual brain regions, severely constraining the understanding of the brain's spatial navigation mechanisms. In this study, synchronized detection of dual‐brain region spatial encoding was conducted using brain–computer interface (BCI). Therefore, an implantable microelectrode array (MEA) was developed tailored for the simultaneous detection of neuronal activities in the CA1 of the hippocampus and the Barrel Cortex (BC) of the somatosensory cortex in rats as BCI. The MEA was improved by modifying the nanocomposite PtNP/PEDOT:PSS to improve their electrical properties (reducing impedance from 1.82 ± 0.17 MΩ to 3.4 ± 0.3 kΩ), facilitating neural recordings in freely behaving rats. The neural activities were obtained from the CA1 and the BC simultaneously and validated the existence of place cells in both brain regions. This study highlighted the potential of PtNP/PEDOT:PSS‐modified MEA as BCI in concurrently detecting neural activity associated with spatial encoding in two brain regions, offering novel perspectives on the processing of tactile stimuli and the formation of cognitive maps for navigation.

Open-set 3D semantic instance maps for vision language navigation – O3D-SIM

Humans excel at forming mental maps of their surroundings, equipping them to understand object relationships and navigate based on language queries. Our previous work SI Maps (Nanwani L, Agarwal A, Jain K, et al. Instance-level semantic maps for vision language navigation. In: 2023 32nd IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). IEEE; 2023 Aug.) showed that having instance-level information and the semantic understanding of an environment helps significantly improve performance for language-guided tasks. We extend this instance-level approach to 3D while increasing the pipeline's robustness and improving quantitative and qualitative results. Our method leverages foundational models for object recognition, image segmentation, and feature extraction. We propose a representation that results in a 3D point cloud map with instance-level embeddings, which bring in the semantic understanding that natural language commands can query. Quantitatively, the work improves upon the success rate of language-guided tasks. At the same time, we qualitatively observe the ability to identify instances more clearly and leverage the foundational models and language and image-aligned embeddings to identify objects that, otherwise, a closed-set approach wouldn't be able to identify. Project Page - https://smart-wheelchair-rrc.github.io/o3d-sim-webpage

Enhancing Accessibility: A Heuristic Evaluation of Social Presence Interface Design for E-Resources in University Libraries

In this preliminary investigation, a discerning evaluation reveals that users face pervasive challenges accessing e-resources within university libraries. A social presence interface design for e-resources is introduced, recognizing the need for user support through effective communication with librarians and assistance for swift information navigation and system function. This research presents a meticulous usability assessment grounded in heuristic evaluation, engaging six expert evaluators comprising specialists in human-computer interaction and librarians. The primary objective is to ascertain the intuitiveness of the interface design and identify potential issues through expert scrutiny. The study unveiled compelling insights by employing a tailored usability heuristic questionnaire encompassing 39 questions aligned with the developed design. Notably, 75.54% of evaluators agreed unanimously regarding the design’s adherence to heuristic principles, indicating their concurrence with the established criteria. Additionally, evaluators provided valuable commentary and feedback focusing on aspects related to icons, labels, and the efficacy of the help function. This comprehensive evaluation informs and enhances the ongoing discourse surrounding optimal user interface design for e-resources in university library settings.