Study of Obstacle-Crossing and Pitch Control Characteristic of a Novel Jumping Robot.
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ABSTRACT:
SUBMITTER: Mo J
PROVIDER: S-EPMC8037127 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The development of autonomous legged/wheeled robots with the ability to navigate and execute tasks in unstructured environments is a well-known research challenge. In this work we introduce a methodology that permits a hybrid legged/wheeled platform to realize terrain traversing functionalities that are adaptable, extendable and can be autonomously selected and regulated based on the geometry of the perceived ground and associated obstacles. The proposed methodology makes use of a set of terrain traversing primitive behaviors that are used to perform driving, stepping on, down and over and can be adapted, based on the ground and obstacle geometry and dimensions. The terrain geometrical properties are first obtained by a perception module, which makes use of point cloud data coming from the LiDAR sensor to segment the terrain in front of the robot, identifying possible gaps or obstacles on the ground. Using these parameters the selection and adaption of the most appropriate traversing behavior is made in an autonomous manner. Traversing behaviors can be also serialized in a different order to synthesise more complex terrain crossing plans over paths of diverse geometry. Furthermore, the proposed methodology is easily extendable by incorporating additional primitive traversing behaviors into the robot mobility framework and in such a way more complex terrain negotiation capabilities can be eventually realized in an add-on fashion. The pipeline of the above methodology was initially implemented and validated on a Gazebo simulation environment. It was then ported and verified on the CENTAURO robot enabling the robot to successfully negotiate terrains of diverse geometry and size using the terrain traversing primitives.
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Project description:BACKGROUND:Community ambulation requires the ability to adapt walking patterns to task demands. For example, complex walking tasks, such as obstacle crossing (OBS) and backwards walking (BW), require modification of gait kinematics to complete the task, maintain stability and prevent falling. More women than men fall each year, but few studies have investigated gender differences in performance of adaptive walking tasks. OBJECTIVE:The purpose of this study was to determine gender differences in two common adaptive tasks. METHODS:Walking performance was assessed from 54 age and gender matched participants (72?±?5?yrs.) while they completed forward walking (FW), OBS and BW. Gait outcomes and the distance of the lead foot and the trail foot from the obstacle were normalized by leg length and assessed using multivariate analysis of variance. Additionally, performance in a battery of clinical physical and cognitive measures as well as self-reported activity levels were associated with adaptive gait behavior. RESULTS:Gait speed and step width were not different between genders in any walking task. Compared to FW and OBS, women only decreased step length in BW, resulting in significantly shorter step lengths than men in OBS (p?=?0.02) and BW (p?=?0.04), a conservative walking strategy. Women crossed the obstacle in a manner that may limit recovery steps in case of a trip: stepping closer to the obstacle during approach without increasing trail toe-clearance. The Timed Up and Go mobility test, Short Physical Performance Battery, and Trail Making Test of processing speed and executive function were associated with gender differences in adaptive gait patterns. CONCLUSION:The findings revealed that older adult women adapt walking in a way that might predispose them to tripping or falling (i.e. shorter steps and closer obstacle approach). Gender differences in adaptive walking are related to functional test performance and processing speed. Clinicians should consider targeting step length during adaptive walking tasks in women that may be at risk of mobility impairments.
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Project description:Obstacle crossing requires visuospatial working memory to guide the trailing leg trajectory when vision in unavailable. Visuospatial working memory, as assessed with neuropsychological tests, declines with age, however, this remains to be investigated functionally in obstacle crossing. There is also evidence that visuospatial encoding during a secondary task interferes with balance control during stepping and walking in older people. Here, we studied the interaction effects of age by delay (study 1) and age by secondary visuospatial task (study 2) conditions on obstacle clearance in a visuospatial working memory -guided obstacle crossing task. Healthy young adults aged 19 to 36 years (n = 20 in study 1 and n = 17 in study 2) and healthy older adults aged 66 to 83 years (n = 29 in study 1 and n = 21 in study 2) were instructed to step over an obstacle with their leading leg and straddle it for a delay period before completing the crossing with their trailing leg. In study 1, two obstacle height conditions (12 cm, 18 cm) and two delay durations (20 s, 60 s) were presented in random order. In study 2, participants were required to attend to either no secondary task (control), a visuospatial secondary (star movement) task, or a nonspatial secondary (arithmetic) task, while straddling the obstacle for a delay duration of 20 s, at obstacle heights of 12 cm and 18 cm, randomly presented. Trailing leg kinematics (mean and variability of maximum toe clearance over the obstacle) were determined via motion capture. There were no statistically significant age by delay or age by secondary task interactions. In study 1, toe clearance variability was significantly greater in young adults and increased with increasing delay duration in both groups. In study 2, compared with the control condition, toe clearance variability was significantly greater in the non-spatial secondary task condition but not in the visuospatial condition. Contrary to our hypotheses, these findings suggest that young and older adults alike can store an obstacle representation via visuospatial working memory for durations of at least 60 s and use this information to safely scale their trailing leg over an obstacle. However, the increase in trailing leg toe clearance variability with delay duration suggests that obstacle representation starts to deteriorate even within the first 20 s regardless of age. The finding that undertaking a concurrent arithmetic task impaired visuospatial working memory-guided obstacle clearance suggests a potential increased risk of tripping during obstacle crossing while dual-tasking in both young and older people.
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Project description:This study aims to compare the differences in the kinematic characteristics of crossing obstacles of different heights between stroke survivors and age-matched healthy controls and to identify the changes of balance control strategy and risk of falling. Twelve stroke survivors and twelve aged-matched healthy controls were recruited. A three-dimensional motion analysis system and two force plates were used to measure the kinematic and kinetic data during crossing obstacles with heights of 10, 20, and 30% leg length. The results showed that during leading and trailing limb clearance, (AP) center of mass (COM) velocities of the stroke group were smaller than those of the healthy controls for all heights. The decreased distances between COM and center of pressure (COP) in the AP direction during the both trailing and leading limb support period were also found between stroke survivors and healthy controls for all heights. The COM velocity and COM-COP distance significantly correlated with the lower limb muscle strength. In addition, stroke survivors showed greater lateral pelvic tilt, greater hip abduction, and larger peak velocity in the medio-lateral (ML) direction. There was a positive correlation between the COM-COP distance in the AP direction and the clinical scales. These results might identify that the stroke survivors used a conservative strategy to negotiate the obstacles and control balance due to a lack of muscle strength. However, the abnormal patterns during obstacle crossing might increase the risk of falling. The findings could be used to design specific rehabilitation training programs to enhance body stability, reduce energy cost, and improve motion efficiency.
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Project description:Large scale operational areas often require multiple service robots for coverage and task parallelism. In such scenarios, each robot keeps its individual map of the environment and serves specific areas of the map at different times. We propose a knowledge sharing mechanism for multiple robots in which one robot can inform other robots about the changes in map, like path blockage, or new static obstacles, encountered at specific areas of the map. This symbiotic information sharing allows the robots to update remote areas of the map without having to explicitly navigate those areas, and plan efficient paths. A node representation of paths is presented for seamless sharing of blocked path information. The transience of obstacles is modeled to track obstacles which might have been removed. A lazy information update scheme is presented in which only relevant information affecting the current task is updated for efficiency. The advantages of the proposed method for path planning are discussed against traditional method with experimental results in both simulation and real environments.
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Project description:Over the last years, the omnipresent standardization of playgrounds-the distances between, for example, jumping stones tend to be equal-has been criticized by both scientists and architects. First, it has been argued that standardization fails to do justice to the variability in the children's action capabilities. Second, it might simplify play in that children repetitively cross over the same distance and, thus, do not have to worry about their movements anymore. In the present study we examined the gap-crossing behavior of children in both a standardized and a nonstandardized jumping stone configuration. Children, between 5 and 10 years of age, were to play in each configuration for two minutes. No significant differences between the configurations were found in the number of gaps the children crossed and the percentage of jumps (ps>0.05). However, more children crossed a gap that they perceived as challenging (i.e. gap width close to their estimated maximum jumping distance) in the nonstandardized configuration than in the standardized one. Interestingly, significant differences were found in variables reflecting the children's action preparation-the variation in both the time on a jumping stone and the numbers of steps on it was bigger in the nonstandardized playground than in the standardized one (ps<0.05). The implications of these findings are discussed for both the design of playgrounds and the academic discussions about them.
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Project description:Several robot-related studies have been conducted in recent years; however, studies on the autonomous travel of small mobile robots in small spaces are lacking. In this study, we investigate the development of autonomous travel for small robots that need to travel and cover the entire smooth surface, such as those employed for cleaning tables or solar panels. We consider an obstacle-available surface and target this travel on it by proposing a spiral motion method. To achieve the spiral motion, we focus on developing autonomous avoidance of obstacles, return to original path, and fall prevention when robots traverse a surface. The development of regular travel by a robot without an encoder is an important feature of this study. The traveled distance was measured using the traveling time. We achieved spiral motion by analyzing the data from multiple small sensors installed on the robot by introducing a new attitude-control method, and we ensured that the robot returned to the original spiral path autonomously after avoiding obstacles and without falling over the edge of the surface.
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Project description:Modern scenarios in robotics involve human-robot collaboration or robot-robot cooperation in unstructured environments. In human-robot collaboration, the objective is to relieve humans from repetitive and wearing tasks. This is the case of a retail store, where the robot could help a clerk to refill a shelf or an elderly customer to pick an item from an uncomfortable location. In robot-robot cooperation, automated logistics scenarios, such as warehouses, distribution centers and supermarkets, often require repetitive and sequential pick and place tasks that can be executed more efficiently by exchanging objects between robots, provided that they are endowed with object handover ability. Use of a robot for passing objects is justified only if the handover operation is sufficiently intuitive for the involved humans, fluid and natural, with a speed comparable to that typical of a human-human object exchange. The approach proposed in this paper strongly relies on visual and haptic perception combined with suitable algorithms for controlling both robot motion, to allow the robot to adapt to human behavior, and grip force, to ensure a safe handover. The control strategy combines model-based reactive control methods with an event-driven state machine encoding a human-inspired behavior during a handover task, which involves both linear and torsional loads, without requiring explicit learning from human demonstration. Experiments in a supermarket-like environment with humans and robots communicating only through haptic cues demonstrate the relevance of force/tactile feedback in accomplishing handover operations in a collaborative task.
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Project description:Avoiding obstacle(s) is a challenging issue in the research of redundant robot manipulators. In addition, noise from truncation, rounding, and model uncertainty is an important factor that affects greatly the obstacle avoidance scheme. In this paper, based on the neural dynamics design formula, a new scheme with the pseudoinverse-type formulation is proposed for obstacle avoidance of redundant robot manipulators in a noisy environment. Such a scheme has the capability of suppressing constant and bounded time-varying noises, and it is thus termed as the noise-tolerant obstacle avoidance (NTOA) scheme in this paper. Theoretical results are also given to show the excellent property of the proposed NTOA scheme (particularly in noise situation). Based on a PA10 robot manipulator with point and window-shaped obstacles, computer simulation results are presented to further substantiate the efficacy and superiority of the proposed NTOA scheme for motion planning of redundant robot manipulators.
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Project description:Compared with the space fixed feature of traditional wireless sensor network (WSN), mobile WSN has better robustness and adaptability in unknown environment, so that it is always applied in the research of target tracking. In order to reach the target, the nodes group should find a self-adaptive method to avoid the obstacles together in their moving directions. Previous methods, which were based on flocking control model, realized the strategy of obstacle avoidance by means of potential field. However, these may sometimes lead the nodes group to fall into a restricted area like a trap and never get out of it. Based on traditional flocking control model, this paper introduced a new cooperative obstacle avoidance model combined with improved SA obstacle avoidance algorithm. It defined the tangent line of the intersection of node's velocity line and the edge of obstacle as the steering direction. Furthermore, the cooperative obstacle avoidance model was also improved in avoiding complex obstacles. When nodes group encounters mobile obstacles, nodes will predict movement path based on the spatial location and velocity of obstacle. And when nodes group enters concave obstacles, nodes will temporarily ignore the gravity of the target and search path along the edge of the concave obstacles. Simulation results showed that cooperative obstacle avoidance model has significant improvement on average speed and time efficiency in avoiding obstacle compared with the traditional flocking control model. It is more suitable for obstacle avoidance in complex environment.
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