Uneven Terrain Research Articles

Burden of Musculoskeletal Pains and Injuries from Water-Carrying Among School-Going Adolescent Girls in Kinshasa’s Peri-Urban Settings, Democratic Republic of Congo

The peri-urban settings of Kinshasa in the Democratic Republic of Congo are mostly characterized by uneven terrain and limited access to water. A cross-sectional epidemiological study of school-going adolescent girls identified public health risks associated with daily water carrying. Data were collected using a semi-structured paper questionnaire, whereas descriptive and regression analysis was performed using SPSS software. The study established that Head-load transportation of water was the most common mode for 92.3% of the interviewed adolescent girls. Compared to other modes, this mode was most likely to expose adolescent girls to musculoskeletal pains and injuries (p < 0.0001). Most adolescent girls interviewed (79.4%) crossed hilly and mountainous terrain. Some 59.4% of adolescent girls experienced falls, 38.6% and 17.4%, respectively, experienced injuries and strains associated with hilly terrain. Almost all the study participants reported pain (96.3%), with 73% reporting back and chest pains. Other reported problems included permanent muscular pain (59.5%), neck pain (55.6%), permanent headaches (50.6%), lower abdominal pain (23.1%), and prolonged painful menstruation (6.7%). Although these data are based on self-reported pain and injuries, their effects could negatively impact adolescent girls’ school attendance and performance. Evidence from this research first supports policies that provide home water supply systems. Such a supply system offers the advantage of relieving the burden of transporting heavy loads of water over long distances and mountainous terrains. Second, evidence demonstrates that the city of Kinshasa struggles to achieve the 6th SDG, which implies negative impacts on the 3rd and 4th SDGs related to health and equitable education for adolescent girls.

Open source robot localization for nonplanar environments

AbstractThe operational environments in which a mobile robot executes its missions often exhibit nonflat terrain characteristics, encompassing outdoor and indoor settings featuring ramps and slopes. In such scenarios, the conventional methodologies employed for localization encounter novel challenges and limitations. This study delineates a localization framework incorporating ground elevation and incline considerations, deviating from traditional two‐dimensional localization paradigms that may falter in such contexts. In our proposed approach, the map encompasses elevation and spatial occupancy information, employing Gridmaps and Octomaps. At the same time, the perception model is designed to accommodate the robot's inclined orientation and the potential presence of ground as an obstacle, besides usual structural and dynamic obstacles. We provide an implementation of our approach fully working with Nav2, ready to replace the baseline Adaptative Monte Carlo Localization (AMCL) approach when the robot is in nonplanar environments. Our methodology was rigorously tested in both simulated environments and through practical application on actual robots, including the Tiago and Summit XL models, across various settings ranging from indoor and outdoor to flat and uneven terrains. Demonstrating exceptional precision, our approach yielded error margins below 10 cm and 0.05 radians in indoor settings and less than 1.0 m in extensive outdoor routes. While our results exhibit a slight improvement over AMCL in indoor environments, the enhancement in performance is significantly more pronounced when compared to three‐dimensional simultaneous localization and mapping algorithms. This underscores the considerable robustness and efficiency of our approach, positioning it as an effective strategy for mobile robots tasked with navigating expansive and intricate indoor/outdoor environments.

Prefrontal cortical activity during uneven terrain walking in younger and older adults.

Walking in complex environments increases the cognitive demand of locomotor control; however, our understanding of the neural mechanisms contributing to walking on uneven terrain is limited. We used a novel method for altering terrain unevenness on a treadmill to investigate the association between terrain unevenness and cortical activity in the prefrontal cortex, a region known to be involved in various cognitive functions. Prefrontal cortical activity was measured with functional near infrared spectroscopy while participants walked on a novel custom-made terrain treadmill surface across four different terrains: flat, low, medium, and high levels of unevenness. The assessments were conducted in younger adults, older adults with better mobility function and older adults with worse mobility function. Mobility function was assessed using the Short Physical Performance Battery. The primary hypothesis was that increasing the unevenness of the terrain would result in greater prefrontal cortical activation in all groups. Secondary hypotheses were that heightened prefrontal cortical activation would be observed in the older groups relative to the younger group, and that prefrontal cortical activation would plateau at higher levels of terrain unevenness for the older adults with worse mobility function, as predicted by the Compensation Related Utilization of Neural Circuits Hypothesis. The results revealed a significant main effect of terrain, indicating a significant increase in prefrontal cortical activation with increasing terrain unevenness during walking in all groups. A significant main effect of group revealed that prefrontal cortical activation was higher in older adults with better mobility function compared to younger adults and older adults with worse mobility function in all pooled terrains, but there was no significant difference in prefrontal cortical activation between older adults with worse mobility function and younger adults. Contrary to our hypothesis, the older group with better mobility function displayed a sustained increase in activation but the other groups did not, suggestive of neural compensation. Additional findings were that task-related increases in prefrontal cortical activation during walking were lateralized to the right hemisphere in older adults with better mobility function but were bilateral in older adults with worse mobility function and younger adults. These findings support that compared to walking on a flat surface, walking on uneven terrain surfaces increases demand on cognitive control resources as measured by prefrontal cortical activation.

A 2‐Dimensional Data Detrending Technique for Equatorial Plasma Bubble Studies Using GOLD Far Ultraviolet Observations

AbstractWe formulate a numerical data detrending technique that can be used to help reveal large‐scale equatorial plasma bubble (EPB) structures in 2‐dimensional data from the Global‐scale Observations of the Limb and Disk (GOLD) mission. This GOLD data detrending technique is inspired by and is a generalization of a previous rolling‐barrel data detrending method for 1‐dimensional total electron content (TEC) observations on individual global positioning system (GPS) satellite passes. This 2‐dimensional GOLD data detrending technique treats the observed 135.6 nm radiance as a function of longitude and latitude as an uneven terrain, where EPBs appear as deep but narrow elongated valleys. The unperturbed background radiance is inferred by rolling a ball on the 2‐dimensional terrain to skip over the EPB valleys. The two degrees‐of‐freedom possessed by the rolling ball allow it to smoothly trace the edges of EPB depletions, without falling into the deep valleys. Surface interpolation of radiance values at the ball's contact points onto the whole domain produces the baseline radiance. Subtracting the baseline from the original radiance data yields the net detrended radiance. As a result of the detrending, sharper contrast is present between EPB depletions and the ambient surroundings. As such, this new 2‐dimensional GOLD data detrending may potentially open the door to the development of other more advanced techniques for automated EPB detection and tracking, or data assimilation into low‐latitude space domain awareness (SDA) information ecosystems.

A toe-inspired rigid-flexible coupling wheel design method for improving the terrain adaptability of a sewer robot.

The human toe, characterized by its rigid-flexible structure comprising hard bones and flexible joints, facilitates adaptive and stable movement across varied terrains. In this paper, we utilized a motion capture system to study the adaptive adjustments of toe joints when encountering obstacles. Inspired by the mechanics of toe joints, we proposed a novel design method for a rigid-flexible coupled wheel. The wheel comprises multiple elements: a rigid skeleton, supporting toes, connecting shafts, torsion springs, soft tendons, and damping pads. The torsion springs connect the rigid frame to the supporting toes, enabling them to adapt to uneven terrains and pipes with different diameters. The design was validated through kinematic and dynamic modeling, rigid-flexible coupled dynamics simulation, and stress analysis. Different stiffness coefficients of torsion springs were compared for optimal wheel design. Then, the wheel was applied to a sewer robot, and its performance was evaluated and compared with a pneumatic rubber tire in various experiments, including movement on flat surfaces, overcoming small obstacles, adaptability tests in different terrains, and active driving force tests in dry and wet pipelines. The results prove that the designed wheel showed better stability and anti-slip properties than conventional tires, making it suitable for diverse applications such as pipeline robots, desert vehicles, and lunar rovers.

Comparative Study on Simulated Outdoor Navigation for Agricultural Robots.

This research presents a comprehensive comparative analysis of SLAM algorithms and Deep Neural Network (DNN)-based Behavior Cloning (BC) navigation in outdoor agricultural environments. The study categorizes SLAM algorithms into laser-based and vision-based approaches, addressing the specific challenges posed by uneven terrain and the similarity between aisles in an orchard farm. The DNN-based BC navigation technique proves efficient, exhibiting reduced human intervention and providing a viable alternative for agricultural navigation. Despite the DNN-based BC navigation approach taking more time to reach its target due to a constant throttle limit for steady speed, the overall performance in terms of driving deviation and human intervention is notable compared to conventional SLAM algorithms. We provide comprehensive evaluation criteria for selecting optimal techniques for outdoor agricultural navigations. The algorithms were tested in three different scenarios: Precision, Speed, and Autonomy. Our proposed performance metric, P, is weighted and normalized. The DNN-based BC algorithm showed the best performance among the others, with a performance of 0.92 in the Precision and Autonomy scenarios. When Speed is more important, the RTAB-Map showed the best score with 0.96. In a case where Autonomy has a higher priority, Gmapping also showed a comparable performance of 0.92 with the DNN-based BC.

Using mobile eye tracking to measure cognitive load through gaze behavior during walking in lower limb prosthesis users: A preliminary assessment

BackgroundLower limb amputation does not affect only physical and psychological functioning but the use of a prosthetic device can also lead to increased cognitive demands. Measuring cognitive load objectively is challenging, and therefore, most studies use questionnaires that are easy to apply but can suffer from subjective bias. Motivated by this, the present study investigated whether a mobile eye tracker can be used to objectively measure cognitive load by monitoring gaze behavior during a set of motor tasks. MethodsFive prosthetic users and eight able-bodied controls participated in this study. Eye tracking data and kinematics were recorded during a set of motor tasks (level ground walking, walking on uneven terrain, obstacle avoidance, stairs up and ramp down, as well as ramp up and stairs down) while the participants were asked to focus their gaze on a visual target for as long as possible. Target fixation times and increase in pupil diameters were determined and correlated to subjective ratings of cognitive load. FindingsOverall, target fixation time and pupil diameter showed strong negative and positive correlations, respectively, to the subjective rating of cognitive load in the able-bodied controls (−0.75 and 0.80, respectively). However, the individual correlation strength, and in some cases, even the sign, was different across participants. A similar trend could be observed in prosthetic users. InterpretationThe results of this study showed that a mobile eye tracker may be used to estimate cognitive load in prosthesis users during locomotor tasks. This paves the way to establish a new approach to assessing cognitive load, which is objective and yet practical and simple to administer. Nevertheless, future studies should corroborate these results by comparing them to other objective measures as well as focus on translating the proposed approach outside of a laboratory.

Influence of Walking Over Unexpected Uneven Terrain on Joint Loading for Individuals With Transtibial Amputation.

Individuals with transtibial amputation (TTA) experience asymmetric lower-limb loading which can lead to joint pain and injuries. However, it is unclear how walking over unexpected uneven terrain affects their loading patterns. This study sought to use modeling and simulation to determine how peak joint contact forces and impulses change for individuals with unilateral TTA during an uneven step and subsequent recovery step and how those patterns compare to able-bodied individuals. We expected residual limb loading during the uneven step and intact limb loading during the recovery step would increase relative to flush walking. Further, individuals with TTA would experience larger loading increases compared to able-bodied individuals. Simulations of individuals with TTA showed during the uneven step, changes in joint loading occurred at all joints except the prosthetic ankle relative to flush walking. During the recovery step, intact limb joint loading increased in early stance relative to flush walking. Simulations of able-bodied individuals showed large increases in ankle joint loading for both surface conditions. Overall, increases in early stance knee joint loading were larger for those with TTA compared to able-bodied individuals during both steps. These results suggest that individuals with TTA experience altered joint loading patterns when stepping on uneven terrain. Future work should investigate whether an adapting ankle-foot prosthesis can mitigate these changes to reduce injury risk.

Performance Evaluation of DGNSS Receiver for Dynamic Military Applications

In military applications, a highly accurate and precise navigation system is necessary for some ground-based combat system applications to navigate the vehicle and mark the location of the fuses and pickets laid by the mobile equipment. Few companies across the globe have developed expertise in manufacturing Global Navigation Satellite System (GNSS) receivers with Real Time Kinematics (RTK) capability along with integrated INS. On mobile equipment, it is not always possible to precisely place the Differential GNSS (DGNSS) antenna and GNSS receiver at the point for which the data needs to be marked. For such applications, lever arm calculation needs to be implemented. Also, due to uneven terrain conditions and slopes, the vehicle undulates up to 10o about its longitudinal and transverse axis. This dynamic condition induces considerable errors in the actual data. During the fuse laying process, there is also a continuous requirement for real-time location data in the GNSS-denied environment for a short period. INS was integrated with the GNSS receiver. We discuss test methodology for GNSS receiver performance evaluation. Experimentations were performed, taking into consideration these requirements. Data collected are also analyzed and discussed. Test results confirmed that the module is accurate with an accuracy of a few centimeters.

Micro-hexapod robot with an origami-like SU-8-coated rigid frame

AbstractIn recent years, many microrobots have been developed for search applications using swarms in places where humans cannot enter, such as disaster sites. Hexapod robots are suitable for moving over uneven terrain. In order to use micro-hexapod robots for swarm exploration, it is necessary to reduce the robot’s size while maintaining its rigidity. Herein, we propose a micro-hexapod with an SU-8 rigid frame that can be assembled from a single sheet. By applying the SU-8 coating as a structure to the hexapod and increasing the rigidity, the substrate size can be reduced to within 40 mm × 40 mm and the total length when assembled to approximately 30 mm. This enables the integration of the micro electromechanical systems (MEMS) process into small and inexpensive hexapod robots. In this study, we assembled the hexapod with a rigid frame from a sheet created using the MEMS process and evaluated the leg motion.

Integrated Modular Neural Control for Versatile Locomotion and Object Transportation of a Dung Beetle-Like Robot.

Dung beetles can effectively transport dung pallets of various sizes in any direction across uneven terrain. While this impressive ability can inspire new locomotion and object transportation solutions in multilegged (insect-like) robots, to date, most existing robots use their legs primarily to perform locomotion. Only a few robots can use their legs to achieve both locomotion and object transportation, although they are limited to specific object types/sizes (10%-65% of leg length) on flat terrain. Accordingly, we proposed a novel integrated neural control approach that, like dung beetles, pushes state-of-the-art insect-like robots beyond their current limits toward versatile locomotion and object transportation with different object types/sizes and terrains (flat and uneven). The control method is synthesized based on modular neural mechanisms, integrating central pattern generator (CPG)-based control, adaptive local leg control, descending modulation control, and object manipulation control. We also introduced an object transportation strategy combining walking and periodic hind leg lifting for soft object transportation. We validated our method on a dung beetle-like robot. Our results show that the robot can perform versatile locomotion and use its legs to transport hard and soft objects of various sizes (60%-70% of leg length) and weights (approximately 3%-115% of robot weight) on flat and uneven terrains. The study also suggests possible neural control mechanisms underlying the dung beetle Scarabaeus galenus' versatile locomotion and small dung pallet transportation.

Design of air-ground cooperative landing platform and autonomous landing strategy

This paper studies innovative design for landing platform design and autonomous landing strategies for unmanned aerial vehicles (UAVs). First, a self-leveling landing platform on a mobile unmanned ground vehicle (UGV) is designed, which can be maintained even when the UGV moves on uneven terrain. Then, with the cooperation of the UAV and the UGV, they are controlled to reach the same velocity in the horizontal direction, which helps avoid the UAV’s rollover caused by horizontal velocity difference. Meanwhile, a buffering strategy is designed to reduce the vertical velocity difference, which helps avoid a hard landing. Finally, a combined landing code is designed to improve the accuracy and success rate of UAV landing. Experiments are carried out to demonstrate the effectiveness of the proposed design of a self-leveling platform and autonomous landing strategies.

Dynamic Fall Recovery Control for Legged Robots via Reinforcement Learning.

Falling is inevitable for legged robots when deployed in unstructured and unpredictable real-world scenarios, such as uneven terrain in the wild. Therefore, to recover dynamically from a fall without unintended termination of locomotion, the robot must possess the complex motor skills required for recovery maneuvers. However, this is exceptionally challenging for existing methods, since it involves multiple unspecified internal and external contacts. To go beyond the limitation of existing methods, we introduced a novel deep reinforcement learning framework to train a learning-based state estimator and a proprioceptive history policy for dynamic fall recovery under external disturbances. The proposed learning-based framework applies to different fall cases indoors and outdoors. Furthermore, we show that the learned fall recovery policies are hardware-feasible and can be implemented on real robots. The performance of the proposed approach is evaluated with extensive trials using a quadruped robot, which shows good effectiveness in recovering the robot after a fall on flat surfaces and grassland.

Kinematic Tripod (K3P): A New Kinematic Algorithm for Gait Pattern Generation

Insects are good examples of ground locomotion because they can adapt their gait pattern to propel them in any direction, over uneven terrain, in a stable manner. Nevertheless, replicating such locomotion skills to a legged robot is not a straightforward task. Different approaches have been proposed to synthesize the gait patterns for these robots; each approach exhibits different restrictions, advantages, and priorities. For the purpose of this document, we have classified gait pattern generators for multi-legged robots into three categories: precomputed, heuristic, and bio-inspired approaches. Precomputed approaches rely on a set of precalculated motion patterns obtained from geometric and/or kinematic models that are performed repeatedly whenever necessary and that cannot be modified on-the-fly to adapt to the terrain changes. On the other hand, heuristic and bio-inspired approaches offer on-line adaptability, but parameter-tuning and heading control can be difficult. In this document, we present the K3P algorithm, a real-time kinematic gait pattern generator conceived to command a legged robot. In contrast to other approaches, K3P enables the robot to adapt its gait to follow an arbitrary trajectory, at an arbitrary speed, over uneven terrain. No precomputed motions for the legs are required; instead, K3P modifies the motion of all mechanical joints to propel the body of the robot in the desired direction, maintaining a tripod stability at all times. In this paper, all the specific details of the aforementioned algorithm are presented, as well as different simulation results that validate its characteristics.

Moving mountains: Geography, neighborhood sorting, and spatial income segregation

AbstractUsing a novel geospatial panel combined with data from the 2015 American Community Survey (ACS), we investigate the effect of topography—altitude and terrain unevenness—on income segregation at the neighborhood level. Specifically, we perform large‐scale counterfactual simulations by estimating household preferences for topography, altering the topographical profile of each city, and observing the resulting neighborhood sorting outcome. We find that unevenness contributes to the segmentation of markets: in the absence of hilliness, rich and poor households experience greater mixing. Hillier cities are more income‐segregated because of their unevenness; the opposite is true for flatter cities.

Accurate Height Determination in Uneven Terrains with Integration of Global Navigation Satellite System Technology and Geometric Levelling: A Case Study in Lebanon

The technology for determining a point’s coordinates on the earth’s surface using the global navigation satellite system (GNSS) is becoming the norm along with ground-based methods. In this case, determining coordinates does not cause any particular difficulties. However, to identify normal heights using this technology with a given accuracy, special research is required. The fact is that satellite determinations of geodetic heights (h) over an ellipsoid surface differ from ground-based measurements of normal height (HN) over a quasi-geoid surface by a certain value called quasi-geoid height or height anomaly (ζ). In relation to determining heights of a certain territory, the concept of geoid height (N) is usually operated when dealing with a geoid model. In this work, geodetic and normal heights are determined for five control points in three different regions in Lebanon, where measurements are carried out using GNSS technology and geometric levelling. The obtained quasi-geoid heights are compared with geoid heights derived from the global Earth model EGM2008. The results obtained showed that, in the absence of gravimetric data, the combination of global Earth model data, geometric levelling for selected areas, and satellite determinations allows for the creation of a highly accurate altitude network for mountainous areas.

Design and Lateral Stability Analysis of an Attitude Adjustment Tractor for Moving on Side Slopes

Lateral overturns are the most frequent fatal accidents involving tractors. A tractor being able to travel safely on uneven or sloped terrain is still an open field of investigation. The design concept of a four-wheel-drive tractor that can traverse hilly and mountainous areas is described. The tractor’s locomotion system can actively adjust its roll angle by using the attitude adjustment mechanisms equipped on the rear wheels. With double quadrangle mechanisms, the front axle can cooperate with the rear axle to adjust this tractor’s attitude. This tractor can also level its body, steer, and transmit power. The principles and configurations of the two axles are presented. A mathematics/mechanical model of a tractor on lateral slopes was developed. This model considers the relationships of the ground supporting forces when the tractor adjusts its roll angle. Combining the model of specific attitude adjustment mechanisms and the above mechanics model, the lateral stability analysis associated with the active input of the attitude adjustment mechanism is conducted. The reliability of the proposed model is discussed based on a comparison of slope traversing experiments and numerical simulations. This designed tractor has potential application in the fields of hilly and mountainous terrains. The results show that posture/configuration adjustment is a positive way to enhance tractor lateral overturn stability.

Spring Less Suspension using Rocker Bogie Mechanism

The rocker bogie mechanism is a type of suspension system commonly used in robotic vehicles, particularly in space exploration rovers like NASA’s Mars rovers. Unlike traditional spring-based suspensions, the rocker bogie mechanism relies on a system of pivoting joints and linkages to maintain stability and traction over uneven terrain. This mechanism allows the vehicle to traverse rough surfaces by distributing weight and adjusting wheel positions to accommodate obstacles. Its abstract nature lies in its ability to provide stability and mobility without relying on springs, making it well-suited for navigating challenging environments such as rocky terrain or steep slopes. Overall, the rocker bogie suspension system is well-suited for applications where stability, mobility, and reliability are paramount, making it a preferred choice for planetary exploration missions and other off-road vehicles operating in rugged terrain

Terrain-Shape-Adaptive Coverage Path Planning With Traversability Analysis

Coverage path planning (CPP) is in great demand with applications in agriculture, mining, manufacturing, etc. Most research in this area focused on 2D CPP problems solving the coverage problem with irregular 2D maps. Comparatively, CPP on uneven terrains is not fully solved. When there are many slopy areas in the working field, it is necessary to adjust the path shape and make it adapt to the 3D terrain surface to save energy consumption. This article proposes a terrain-shape-adaptive CPP method with three significant features. First, the paths grow by themselves according to the local terrain surface shapes. Second, the growth rule utilizes the 3D terrain traversability analysis, which makes them automatically avoid entering hazardous zones. Third, the irregularly distributed paths are connected under an optimal sequence with an improved genetic algorithm. As a result, the method can provide an autonomously growing terrain-adaptive coverage path with high energy efficiency and coverage rate compared to previous research works. It is demonstrated on various maps and is proven to be robust to terrain conditions.

Electrical brain activity during human walking with parametric variations in terrain unevenness and walking speed

Abstract Mobile brain imaging with high-density electroencephalography (EEG) can provide insight into the cortical processes involved in complex human walking tasks. While uneven terrain is common in the natural environment and poses challenges to human balance control, there is limited understanding of the supraspinal processes involved with traversing uneven terrain. The primary objective of this study was to quantify electrocortical activity related to parametric variations in terrain unevenness for neurotypical young adults. We used high-density EEG to measure brain activity when 32 young adults walked on a novel custom-made uneven terrain treadmill surface with four levels of difficulty at a walking speed tailored to each participant. We identified multiple brain regions associated with uneven terrain walking. Alpha (8 - 13 Hz) and beta (13 - 30 Hz) spectral power decreased in the sensorimotor and posterior parietal areas with increasing terrain unevenness while theta (4 - 8 Hz) power increased in the mid/posterior cingulate area with terrain unevenness. We also found that within stride spectral power fluctuations increased with terrain unevenness. Our secondary goal was to investigate the effect of parametric changes in walking speed (0.25 m/s, 0.5 m/s, 0.75 m/s, 1.0 m/s) to differentiate the effects of walking speed from uneven terrain. Our results revealed that electrocortical activities only changed substantially with speed within the sensorimotor area but not in other brain areas. Together, these results indicate there are distinct cortical processes contributing to the control of walking over uneven terrain versus modulation of walking speed on smooth, flat terrain. Our findings increase our understanding of cortical involvement in an ecologically valid walking task and could serve as a benchmark for identifying deficits in cortical dynamics that occur in people with mobility deficits.