Navigation Challenges Research Articles

At Crossroads in a Virtual City: Effect of Spatial Disorientation on Gait Variability and Psychophysiological Response among Healthy Older Adults

Introduction: Aging has been associated with a decline in cognitive and motor performance, often expressed in multitasking situations, which could include wayfinding. A major challenge to successful wayfinding is spatial disorientation, occurring mostly at crossings. Although gait changes have been observed in various dual-task conditions, little is known about the effect of disorientation on gait and psychophysiological response among older adults during wayfinding. The study aimed at identifying the effect of spatial disorientation on gait variability and psychophysiological response among healthy older adults during wayfinding in a controlled environment. Method: We analyzed data of 28 participants (age 70.8 ± 4.6, 18 female), 14 experimental and 14 controls. Participants performed a wayfinding task consisting of 14 major decision points (7 intersections) within a virtual environment (VE) projected on a 180° screen while walking on a self-paced treadmill equipped with a marker-based optical motion-capture system. The VE was held constant for the controls and manipulated for the experimental participants. Disorientation was identified based on a customized annotation scheme. Variability in gait, including the coefficient of variation (CV), was measured as the primary endpoint. Psychophysiological response measures, including heart rate variability (RMSSD) and skin conductance response (SCR), were continuously monitored as secondary endpoints and estimates of cognitive effort. Linear Mixed Effects models were applied to hypothesis-driven outcome measures extracted from decision points. Results: Walking speed and step length decreased when disoriented (p < 0.05), while stride time, stance time, walking speed CV, stance time CV, SCR amplitude, and SCR count increased when disoriented (p < 0.05). A higher RMSSD was associated with being disoriented at crossings (p < 0.05). SCR count was greater in the older experimental group (p < 0.001), including when disoriented (p < 0.001). Discussion/Conclusion: The results provide evidence for the impact of spatial disorientation on changes in gait pattern and psychophysiological response among older adults during wayfinding. Location also had implications for the effect of disorientation on gait and cognitive effort. This gives further insight into the substrates of real-world navigation challenges among older adults, with an emphasis on viable features for designing situation-adaptive interventional devices aiding independent mobility.

The navigational challenges of a blended learning approach to teaching in business and management

This paper contributes an assessment of academic perceptions and agency in relation to blended learning. Digital technology provides management educators with opportunities for new and distinctive learning and teaching models. Qualitative semi-structured interview data gathered from academics from different business specialisms provides the basis for analysis of their reflections about their navigation of blended learning and factors that affect its adoption as a feature of business school pedagogy. Results indicate that academic reflexivity, social interaction, and agency, in dynamic combination, are important to understand and explain academics’ navigation of blended learning as a feature of pedagogy. The article contributes new knowledge about factors that affect the deployment of blended learning in business school contexts. It contributes to theory by extending conceptualization of academic reflexivity and agency. It discusses implications for academics and policy makers who are involved in introducing blended learning in management education contexts.

Autonomous Ground Navigation in Highly Constrained Spaces: Lessons Learned From the Benchmark Autonomous Robot Navigation Challenge at ICRA 2022 [Competitions

The Benchmark Autonomous Robot Navigation (BARN) Challenge took place at the 2022 IEEE International Conference on Robotics and Automation (ICRA), in Philadelphia, PA, USA. The aim of the challenge was to evaluate state-of-the-art autonomous ground navigation systems for moving robots through highly constrained environments in a safe and efficient manner. Specifically, the task was to navigate a standardized differential drive ground robot from a predefined start location to a goal location as quickly as possible without colliding with any obstacles, both in simulation and in the real world. Five teams from all over the world participated in the qualifying simulation competition, three of which were invited to compete with one another at a set of physical obstacle courses at the conference center in Philadelphia. The competition results suggest that autonomous ground navigation in highly constrained spaces, despite seeming simple for experienced roboticists, is actually far from being a solved problem. In this article, we discuss the challenge, the approaches used by the top three winning teams, and lessons learned to direct future research.

125 STROKE SURVIVOR AND CARER EXPERIENCES OF NAVIGATION OF STROKE SERVICES AND INFORMATION IN IRELAND: AN EXPLORATORY QUALITATIVE INTERVIEW STUDY

Abstract Background Patient navigation of stroke services is challenging, as survivors have diverse and complex needs, and clear care pathways are often lacking, particularly in the post-acute phase. Exploring the views of stroke survivors and main carers is critical to understanding these navigational challenges. Methods In-depth semi-structured interviews were conducted online or by phone with stroke survivors (n=16) and main carers (n=13) recruited through voluntary organisations and social media. Participants with communication or cognitive difficulties were included, and provided with accessible information materials. Interviews were audio-recorded and transcribed. Framework analysis was used, involving data familiarisation, coding, development of an analytic framework, charting and interpretation. Ryvicker’s (2018) behavioral-ecological conceptual framework for patient navigation was used to inform the analytic framework. Results Barriers to successful patient navigation at the healthcare system level included complex and unclear eligibility criteria for services and entitlements, including arbitrary age limits; geographical variation; and waiting times for services, particularly rehabilitation. Having a skilled or knowledgeable advocate, such as a family member with experience of the healthcare system, was a key enabling factor. Survivors and carers had to be pro-active and “push” or “battle” for needed services and information. Navigation often involved a substantial administrative burden, which survivors and caregivers had to manage in addition to the demands of the stroke itself, the recovery process, and in many cases other co-morbidities. Healthcare provider factors that supported navigation included clear communication with survivors/carers about services and the stroke itself. Staff who specifically supported care co-ordination were helpful, but this tended to be ad-hoc and limited in availability. Conclusion Dedicated staff to support patient navigation across the care continuum could make a significant difference to stroke survivor access to services and consequently outcomes. Clearer, standardised and more person-centred referrals pathways, that are widely publicised and understood, would also improve access.

How social capital enabled healthcare access and navigation by vulnerable people during Covid-19

Abstract Background Healthcare systems have become complex and fragmented, negatively affecting healthcare access and navigation. This is especially the case for socio-economically vulnerable people, who encounter organisational and administrative hindrances trying to access care. These difficulties have worsened during Covid-19. Scholarly literature recognises that - by moulding navigation practices - social capital may mediate between potential and realised access to healthcare. However, little is known about how this mediating work practically unfolds. Methods This case study aimed to understand how social capital might affect healthcare navigation practices. To do so, we investigated how the People’s Health Lab (PHL), a community-based organisation, supported socio-economically vulnerable people in navigating healthcare during the Covid-19 pandemic in Bologna, Italy. Nine months of participant observation were conducted both in person and digitally from July 2020 to March 2021. Twelve semistructured interviews were also conducted with volunteers of the organisation. Fieldnotes and interview transcripts were analysed through Thematic Analysis. Results PHL support activities addressed barriers to healthcare navigation by vulnerable people, which were found to be services fragmentation, bureaucracy and Covid-19 restrictions. Volunteers of the PHL connected vulnerable individuals to health services in manifold, flexible ways, working without standard operative protocols and relying on informal personal contacts within public services. This was found to be key in enabling navigation of healthcare during the first three waves of the pandemic. Conclusions Our study provides evidence about how structural, linking social capital - the material and nonmaterial resources mobilised through the relationships between heterogeneous groups (the People’s Health Lab, health authorities and vulnerable people) - can mediate access to fragmented healthcare systems by shaping navigation practices. Key messages • Contemporary healthcare systems – including universal ones – have become complex and fragmented, posing access and navigation challenges to their users, especially those socio-economically vulnerable. • Linking social capital can mediate access to fragmented healthcare systems by flexibly mobilising material and nonmaterial resources through informal relationships between heterogeneous groups.

Informing care pathways and policies for children and youth with Indigenous perspectives to advance Canada's National Autism Strategy.

In Canada, most services for Autistic people are provided by provincial and territorial governments. However, support for Indigenous Peoples (First Nations, Inuit, and Métis) are under federal responsibility and are outlined by a set of treaties and agreements with the Crown and a few regional governments. This patchwork results in barriers in service access and navigation challenges in many under-resourced communities, including under-diagnosis and potentially life-threatening outcomes. Designing equitable policy structures and processes would reduce harms and meaningfully interface with Indigenous and other racialized communities. The objective of this Policy Practice Review is to provide a framework for the discovery of appropriate care strategies addressing the conceptualization of autism in Indigenous Peoples and to understand the interactions between racialized Autistic peoples and the Criminal Justice System. First, we conducted environmental scans of publicly-accessible government services available in Canada pertaining to autism in Indigenous communities and the justice system, and explored the dissonance with beliefs and perceptions of autism in Northern Indigenous communities. Second, we focused on the interactions of Indigenous and other racialized populations, with an emphasis on Autistic children and youth with the justice system, an interaction that is often life-altering, downstream, and detrimental to health and wellbeing. The implications of this work include identifying the need for Indigenous-led knowledge and policy recommendations for Canada's upcoming National Autism Strategy, informing the need for culturally appropriate multidisciplinary care and facilitating the coordination between health and social services for these communities.

Multi-Objective Instantaneous Center of Rotation Optimization Using Sensors Feedback for Navigation in Self-Reconfigurable Pavement Sweeping Robot

Pavement in outdoor settings is an unstructured environment with sharp corners, varying widths, and pedestrian activity that poses navigation challenges while cleaning for autonomous systems. In this work, an approach towards navigating without collision in constrained pavement spaces using the optimal instantaneous center of rotation (ICR) is demonstrated using an in-house developed omnidirectional reconfigurable robot named Panthera. The Panthera reconfigurable design results in varying footprints, supported by passive linear joints along the robot width, with locomotion and steering action using four wheels independent steering drive (4WISD). The robot kinematics and perception sensors system are discussed. Further, the ICR selection is carried out using multi-objective optimization, considering functions for steering, varying width, distance, and clearance to avoid a collision. The framework is incorporated in a local navigation planner and demonstrated experimentally in real pavement settings. The results with optimal selection of ICR in two dimensional space within the robot footprint successfully perform smooth navigation in the constraint space. It is experimentally highlighted with four different scenarios, i.e., constraint conditions encountered by a robot during navigation. Moreover, the formulation of optimal selection of ICR while avoiding collision is generic and can be used for other mobile robot architectures.

A Beacons Selection Method under Random Interference for Indoor Positioning

GNSS is still not well applied in indoor environments. This is an important challenge for seamless positioning and navigation. Using other sensors to replace and connect is the mainstream practice at present. No matter what technology is used, the problem of real-time optimal station selection is faced in complex indoor environments. In this paper, we first verified the impact of random interference from walkers on positioning signals in an indoor environment. Based on this phenomenon, we proposed a novel real-time dynamic Beacons selection method (RD) in the field of indoor positioning. First, we introduced a machine learning algorithm for real-time anomaly detection of received signals from different Beacons. Then the Beacon selection is completed based on the real-time anomaly detection results and RSSI. In an indoor scene, we verified the positioning accuracy of three other methods when selecting various numbers of Beacons. Then we used the best selection strategies to compare with the RD method. Experiments showed that the RD method can use the least Beacons to obtain higher accuracy and stable positioning results. This paper provides a new idea for real-time optimal selection of signal sources in a complex indoor environment.

Annotation-guided encoder-decoder network for bone extraction in ultrasound-assisted orthopedic surgery

The patients and surgeons are usually exposed in massive ionizing radiation during fluoroscopy-based navigation orthopedic surgery. Comparatively, ultrasound-assisted orthopedic surgery could not only decrease the risk of radiation but also provide rich navigation information. However, due to the artifacts in ultrasound images, the extraction of bone structure from ultrasound sequences can be a particularly difficult task, which leads to some major challenges in ultrasound-assisted orthopedic navigation. In this paper, we propose an annotation-guided encoder-decoder network (AGN) to extract bone structure from the radiation-free ultrasound sequences. Specifically, the variability of the ultrasound probe's pose leads to the change of the ultrasound frame during the acquisition of ultrasound sequences. Therefore, a feature alignment module deployed in the AGN model is used to achieve reliable matching across ultrasound frames. Moreover, inspired by the interactive ultrasound analysis, where user annotated foreground information can help target extraction, our AGN model incorporates the annotation information obtained by Siamese networks. Experimental results validated that the AGN model not only produced better bone surface extraction than state-of-the-art methods (IOU: 0.92 versus. 0.88), but also achieved almost real-time extraction with the speed about 15 frames per second. In addition, the acquired bone surface further provided radiation-free 3D intraoperative bone structure for the intuitive navigation of orthopedic surgery.

EKF-LOAM: An Adaptive Fusion of LiDAR SLAM With Wheel Odometry and Inertial Data for Confined Spaces With Few Geometric Features

A precise localization system and a map that properly represents the environment are fundamental for several robotic applications. Traditional LiDAR SLAM algorithms are particularly susceptible to underestimating the distance covered by real robots in environments with few geometric features. Common industrial confined spaces, such as ducts and galleries, have long and homogeneous structures, which are difficult to map. In this paper, we propose a novel approach, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EKF-LOAM</i> , which fuses wheel odometry and IMU (Inertial Measurement Unit) data into the LeGO-LOAM algorithm using an Extended Kalman Filter. For that, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EKF-LOAM</i> uses a simple and lightweight adaptive covariance matrix based on the number of detected geometric features. Simulated and real-world experiments with the EspeleoRobô, a service robot designed to inspect confined places, show that the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EKF-LOAM</i> method reduces the underestimating problem, with improvements greater than 50% when compared to the original LeGO-LOAM algorithm. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This paper is motivated by the challenges of autonomous navigation for mobile ground robots within confined and unstructured environments. Here, we propose a data fusion framework that uses common sensors (such as LiDARs, wheel odometry, and inertial devices) to improve the simultaneous localization and mapping (SLAM) capabilities of a robot without GPS and compass. This approach does not need artificial landmarks nor ideal light and, in scenarios with few geometric features, increases the performance of LiDAR SLAM techniques based on edge and planar features. We also provide a robust controller for the autonomous navigation of the robot during the mapping of a tunnel. Experiments carried out in simulation and real-world confined places show the effectiveness of our approach. In future work, we shall incorporate other sensors, such as cameras, to improve the SLAM process.

Framework and Evaluation Methodology for Autonomous Drone Racing

In recent years, autonomous drone races have become increasingly popular in the aerial robotics research community due to challenges in perception, localization, navigation, and control at high speeds, pushing forward the state-of-the-art every year. However, autonomous racing drones are still far from reaching human pilot performance, and a lot of research has to be done to accomplish that. In this work, a complete architecture system and an evaluation method for autonomous drone racing research are proposed, based on the Aerostack 5.0 open-source framework. To evaluate the performance of the whole system and of each algorithm used separately, this framework is validated not only with simulated flights, but also through real flights in an indoor drone race circuit using different configurations.

Perceptions of cancer care coordination among rural patients in Hawaii.

e18553 Background: Rural residents experience disproportionate burdens of cancer including higher incidence and mortality than urban residents. Disparities in rural cancer health outcomes are partially attributed to limited access to specialty care and care coordination challenges in rural areas. To date, little is known about rural cancer patients’ perceptions of care coordination (CC). In this study, we examined rural patients’ perceptions of cancer CC and compared rural and urban patients’ perceptions of cancer CC using the Care Coordination Instrument (CCI), a validated patient-report measure of CC. Methods: 80 rural patients receiving active treatment for any cancer residing in rural areas of Hawaii (Hawaii Island, Kauai) completed the CCI from Sept. 2020 to Dec. 2021. These rural areas are on separate islands from Oahu (urban) where tertiary care hospitals in Hawaii are located. Data for the urban cohorts ( n = 220) were derived from our archival data. The CCI assesses overall patients’ perceptions of CC (Total) and includes subscales that evaluate CC across three domains (Communication, Navigation, Operational). We used descriptive statistics to describe rural patients’ CC details and linear regression models to compare CCI scores between rural and urban patients. Results: Among 300 patients, demographic and clinical characteristics were similar between the rural and urban cohorts (mean age = 63.6, 56% female, most common cancer type: 28% breast and 25% GI). Patients were racially diverse, with 25% White/Caucasian, 24% Japanese, 16% Native Hawaiian, and 24% two or more race. Among rural patients, 43% indicated having traveled by air to another island (Oahu; urban) for cancer treatment (50% surgery). Of these patients, 38% indicated having paid out-of-pocket for cancer care-related travel costs. 65% of these patients reported travel costs as a burden, with 6% of patients having canceled or delayed treatment due to costs. Overall, there were no differences on the Total CCI scores between rural and urban patients ( p = 0.73). However, significant differences were found for Communication and Navigation ( p = 0.02 and p = 0.04, respectively), with rural patients reporting lower scores on these domains. No differences were found for the Operational domain scores. Conclusions: Our results demonstrate that that while rural patients’ overall perceptions of CC were similar to their urban cohorts, rural patients perceived greater CC challenges related to the communication and navigation aspects of CC. Off-island cancer care-related travel costs were reported as a significant burden for rural patients who must travel to another island for their cancer treatment. These findings highlight the need for interventions to address financial, communication and navigation challenges for rural patients in order to improve the quality of cancer care delivery in rural areas.

Learning a Robust Hybrid Descriptor for Robot Visual Localization

Long-term robust visual localization is one of the main challenges of long-term visual navigation for mobile robots. Due to factors such as illumination, weather, and season, mobile robots continuously navigate with visual information in a complex scene, which is likely to lead to failure localization within a few hours. However, semantic segmentation images will be more stable than the original images against considerable drastically variable environments; therefore, to make full use of the advantages of both semantic segmentation image and its original image, this paper solves the above problems with the latest work of semantic segmentation and proposes the novel hybrid descriptor for long-term visual localization, which is generated by combining a semantic image descriptor extracted from segmentation images and an image descriptor extracted from RGB images with a certain weight, and then trained by a convolutional neural network. Our experiments show that the localization performance of our method combining the advantages of semantic image descriptor and image descriptor is superior to those long-term visual localization methods with only an image descriptor or semantic image descriptor. Finally, our experimental results mostly exceed state-of-the-art 2D image-based localization methods under various challenging environmental conditions in the Extended CMU Seasons and RobotCar Seasons datasets in specific precision metrics.

Sensor Based Wearable Devices for Road Navigation

Internet of Things (IoT)-based applications play a significant role and are highly influenced by the global positioning system (GPS). GPS has a wide range of applications and benefits in tracking and route finding. A GPS tracker can help to explore numerous possibilities in various domains such as the health field, safety (to protect various assets), pattern recognition, logistics, in business models by using navigation systems embedded with sensors, and many more. Smart IoT wearable devices are the next step of evolution in the field of navigation using visual, auditory, ultrasonic, and other technologies. This paper introduces the various IoT sensors used in navigation systems and some prominent existing applications. This paper also provides a survey of existing wearable devices and concludes that the correct choice of sensors can easily overcome the challenges of navigation.

Resilient and Modular Subterranean Exploration with a Team of Roving and Flying Robots

Subterranean robot exploration is difficult, with many mobility, communications, and navigation challenges that require an approach with a diverse set of systems, and reliable autonomy. While prior work has demonstrated partial successes in addressing the problem, here we convey a comprehensive approach to address the problem of subterranean exploration in a wide range of tunnel, urban, and cave environments. Our approach is driven by the themes of resiliency and modularity, and we show examples of how these themes influence the design of the different modules. In particular, we detail our approach to artifact detection, pose estimation, coordination, planning, control, and autonomy, and we discuss our performance in the tunnel, urban, and self-organized cave circuits of the DARPA Subterranean Challenge. Our approach led to a winning result in the tunnel circuit, and placing second in the urban circuit event. We convey lessons learned in designing and testing a resilient system for subterranean exploration that can generalize to a large range of operating conditions, and potential improvements for the future.

Study protocol: navigating access to gender care in Ireland—a mixed-method study on the experiences of transgender and non-binary youth

IntroductionThere has been a global increase in demand for gender-specific healthcare services and a recognition that healthcare access is complex and convoluted, even in countries with well-developed healthcare services. Despite...

Navigational Experience and the Preservation of Spatial Abilities into Old Age Among a Tropical Forager-Farmer Population.

Navigational performance responds to navigational challenges, and both decline with age in Western populations as older people become less mobile. But mobility does not decline everywhere; Tsimané forager-farmers in Bolivia remain highly mobile throughout adulthood, traveling frequently by foot and dugout canoe for subsistence and social visitation. We, therefore, measured both natural mobility and navigational performance in 305 Tsimané adults, to assess differences with age and to test whether greater mobility was related to better navigational performance across the lifespan. Daily mobility was measured by GPS tracking, regional mobility through interview, navigational performance through pointing accuracy and perspective taking in environmental space, and mental rotation by a computerized task. Although mental rotation and spatial perspective taking declined with age, mobility and pointing accuracy remained high from mid-life through old age. Greater regional mobility was associated with greater accuracy at pointing and perspective taking, suggesting that spatial experience at environmental scales may help maintain navigational performance in later adulthood.

Robust locomotor performance of squirrel monkeys (Saimiri boliviensis) in response to simulated changes in support diameter and compliance.

Arboreal environments require overcoming navigational challenges not typically encountered in other terrestrial habitats. Supports are unevenly distributed and vary in diameter, orientation, and compliance. To better understand the strategies that arboreal animals use to maintain stability in this environment, laboratory researchers must endeavor to mimic those conditions. Here, we evaluate how squirrel monkeys (Saimiri boliviensis) adjust their locomotor mechanics in response to variation in support diameter and compliance. We used high-speed cameras to film two juvenile female monkeys as they walked across poles of varying diameters (5, 2.5, and 1.25 cm). Poles were mounted on either a stiff wooden base ("stable" condition) or foam blocks ("compliant" condition). Six force transducers embedded within the pole trackway recorded substrate reaction forces during locomotion. We predicted that squirrel monkeys would walk more slowly on narrow and compliant supports and adopt more "compliant" gait mechanics, increasing stride lengths, duty factors, and an average number of limbs gripping the support, while the decreasing center of mass height, stride frequencies, and peak forces. We observed few significant adjustments to squirrel monkey locomotor kinematics in response to changes in either support diameter or compliance, and the changes we did observe were often tempered by interactions with locomotor speed. These results differ from a similar study of common marmosets (i.e., Callithrix jacchus, with relatively poor grasping abilities), where variation in diameter and compliance substantially impacted gait kinematics. Squirrel monkeys' strong grasping apparatus, long and mobile tails, and other adaptations for arboreal travel likely facilitate robust locomotor performance despite substrate precarity.

Development of Navigation System for Blind People based on Light Detection and Ranging Technology(LiDAR)

The use of blind-aided navigating systems has become very essential in the 4th industrial revolution. The essence of this is to improve navigating autonomy for the blind. Although, navigation challenges are not of serious concern to people with eye defects. However, this is a major concern for blind people due to the time-consuming navigation process. These limitations necessitate the use of walking sticks, dogs, or people to navigate their path. This project provides a blind navigation system based on Light Detection and Ranging Based Navigation System for Blind People (LiDAR). The components of this fabricated device involve a charging system, a LiDAR sensor, a microcontroller, a calling stick, two buzzers, a switch vibration motor with an RF transmitter, and a receiver to give object detection and real-time assistance to the blind. The mode of its operation is by detecting obstacles along the route of a blind person and giving a notification via the buzzer and the vibration motor. Also, during emergencies, the buzzer rings and informs the visually impaired person using the device. On the other hand, the microcontroller and other modules in the device have a continuous ongoing relationship which is beneficial to the user. Another appreciable benefit of this device is the ability to recharge the battery component, the device is of low-cost, quick, simple-to-use, and novel solution for the blind.

A Hierarchical Approach for Mobile Robot Exploration in Pedestrian Crowd

Autonomous exploration is a fundamental task for mobile robots. However, a major limitation is that in practical applications, robots usually face dynamic obstacles such as pedestrian crowds. These dynamic objects create significant challenges for both collision-free navigation and accurate localization/mapping, which can compromise the safety and exploration performance of the robot. In this work, a hierarchical approach is proposed for both effective exploration and collision-free navigation in crowded environments. The central idea of our approach is to combine local and global information to ensure the safety and efficiency of the exploration planner. Besides, our planning method utilizes a reinforcement learning (RL)-based obstacle avoidance algorithm that allows the robot to safely follow the exploration planner's path through the pedestrian crowd. The proposed system is thoroughly evaluated in simulation environments, and the results show that it outperforms existing methods in terms of not only the exploration efficiency but also the localization and mapping accuracy.