Virtual Obstacle Research Articles

Visual control of foot placement when walking over complex terrain.

The aim of this study was to investigate the role of visual information in the control of walking over complex terrain with irregularly spaced obstacles. We developed an experimental paradigm to measure how far along the future path people need to see in order to maintain forward progress and avoid stepping on obstacles. Participants walked over an array of randomly distributed virtual obstacles that were projected onto the floor by an LCD projector while their movements were tracked by a full-body motion capture system. Walking behavior in a full-vision control condition was compared with behavior in a number of other visibility conditions in which obstacles did not appear until they fell within a window of visibility centered on the moving observer. Collisions with obstacles were more frequent and, for some participants, walking speed was slower when the visibility window constrained vision to less than two step lengths ahead. When window sizes were greater than two step lengths, the frequency of collisions and walking speed were weakly affected or unaffected. We conclude that visual information from at least two step lengths ahead is needed to guide foot placement when walking over complex terrain. When placed in the context of recent research on the biomechanics of walking, the findings suggest that two step lengths of visual information may be needed because it allows walkers to exploit the passive mechanical forces inherent to bipedal locomotion, thereby avoiding obstacles while maximizing energetic efficiency.

Interactive balance training integrating sensor-based visual feedback of movement performance: a pilot study in older adults.

BackgroundWearable sensor technology can accurately measure body motion and provide incentive feedback during exercising. The aim of this pilot study was to evaluate the effectiveness and user experience of a balance training program in older adults integrating data from wearable sensors into a human-computer interface designed for interactive training.MethodsSenior living community residents (mean age 84.6) with confirmed fall risk were randomized to an intervention (IG, n = 17) or control group (CG, n = 16). The IG underwent 4 weeks (twice a week) of balance training including weight shifting and virtual obstacle crossing tasks with visual/auditory real-time joint movement feedback using wearable sensors. The CG received no intervention. Outcome measures included changes in center of mass (CoM) sway, ankle and hip joint sway measured during eyes open (EO) and eyes closed (EC) balance test at baseline and post-intervention. Ankle-hip postural coordination was quantified by a reciprocal compensatory index (RCI). Physical performance was quantified by the Alternate-Step-Test (AST), Timed-up-and-go (TUG), and gait assessment. User experience was measured by a standardized questionnaire.ResultsAfter the intervention sway of CoM, hip, and ankle were reduced in the IG compared to the CG during both EO and EC condition (p = .007-.042). Improvement was obtained for AST (p = .037), TUG (p = .024), fast gait speed (p = . 010), but not normal gait speed (p = .264). Effect sizes were moderate for all outcomes. RCI did not change significantly. Users expressed a positive training experience including fun, safety, and helpfulness of sensor-feedback.ConclusionsResults of this proof-of-concept study suggest that older adults at risk of falling can benefit from the balance training program. Study findings may help to inform future exercise interventions integrating wearable sensors for guided game-based training in home- and community environments. Future studies should evaluate the added value of the proposed sensor-based training paradigm compared to traditional balance training programs and commercial exergames.Trial registrationhttp://www.clinicaltrials.govNCT02043834.Electronic supplementary materialThe online version of this article (doi:10.1186/1743-0003-11-164) contains supplementary material, which is available to authorized users.

Response inhibition during avoidance of virtual obstacles while walking

While walking, one often has to suppress and adjust a planned step in order to avoid a fall. Given that steps are preprogrammed this requires some form of motor inhibition. Motor inhibition is commonly tested in hand function and only recently attempts have been made to evaluate inhibition in the lower limbs, during step initiation. As adequate motor inhibition might play a role in avoiding falls a test to assess response inhibition during walking would be valuable. We developed a task in which subjects walked on a treadmill by stepping on projected patches of light, which could suddenly change color forcing the subjects to avoid it by shortening or lengthening their steps. The difficulty level was manipulated in 4 conditions by changing the distance available to respond. We hypothesized that larger demands on motor inhibition during walking would produce more failures and tested the performance of young adults (n=12) in order to establish the protocol for use in older adults. The failure rate on the walking test was analyzed. Reducing the available response distance by 150 mm from the easiest condition resulted in a significant increase in failure rates from 15.6% to 65.1%. Therefore, results indicate this novel test can be used to assess the level of motor inhibition during walking. Additionally, in comparison to previous literature on obstacle avoidance, our experiment shows that changing a precise aiming movement is considerably more challenging than changing the same movement executed automatically.

Speeded Reaching Movements around Invisible Obstacles

We analyze the problem of obstacle avoidance from a Bayesian decision-theoretic perspective using an experimental task in which reaches around a virtual obstacle were made toward targets on an upright monitor. Subjects received monetary rewards for touching the target and incurred losses for accidentally touching the intervening obstacle. The locations of target-obstacle pairs within the workspace were varied from trial to trial. We compared human performance to that of a Bayesian ideal movement planner (who chooses motor strategies maximizing expected gain) using the Dominance Test employed in Hudson et al. (2007). The ideal movement planner suffers from the same sources of noise as the human, but selects movement plans that maximize expected gain in the presence of that noise. We find good agreement between the predictions of the model and actual performance in most but not all experimental conditions.

Humans exploit the biomechanics of bipedal gait during visually guided walking over rough terrain

When walking over flat terrain, humans achieve remarkable energetic efficiency by exploiting the passive mechanical forces inherent to the biomechanical structure of bipedal locomotion. The idea that energetic efficiency is achieved by exploiting passive forces in the body has gained traction in the field of biomechanics, but no research exists on the way these principles govern the control of walking when vision is needed to guide foot placement. We tested the hypothesis that when walking over rough terrain, vision is used to identify footholds that allow the walker to approximate the efficiency of walking over flat terrain. Subjects walked over an array of randomly distributed virtual obstacles that were projected onto the floor by an LCD projector while their movements were recorded using a full-body motion capture system. Walking behavior was analyzed during a full-vision control condition as well as in a number of other visibility conditions in which obstacles did not appear until they fell within a window of visibility centered on the moving observer. Analyses focused on the relationship between the size of the visibility window and the active (i.e., muscle-generated) forces needed to redirect the center of mass to avoid stepping on obstacles. When the visibility window restricted vision to less than two steps, additional energetically costly active muscular forces were needed to avoid obstacles. When the visibility window allowed vision beyond two steps, active forces dropped to baseline levels observed in the full-vision condition. The findings suggest that visual information from the immediate foreground is used to identify footholds that allow the walker to approximate the energetic efficiency realized when walking over uncluttered terrain. The theoretical framework provided by the dynamic walking approach to gait control suggests an elegant explanation of the functional significance of the two-step distance in the visual control of human walking. Meeting abstract presented at VSS 2012

Virtualizing the Assessment: A Novel Pragmatic Paradigm to Evaluate Lower Extremity Joint Perception in Diabetes

Background: Individuals with diabetes have a higher risk of falls and fall-related injuries. People with diabetes often develop peripheral neuropathy (DPN) as well as nerve damage throughout the body. In particular, reduced lower extremity proprioception due to DPN may cause a misjudgment of foot position and thus increase the risk of fall. Objective: An innovative virtual obstacle-crossing paradigm using wearable sensors was developed in an attempt to assess lower extremity position perception damage due to DPN. Methods: 67 participants (age 55.4 ± 8.9, BMI 28.1 ± 5.8) including diabetics with and without DPN as well as aged-matched healthy controls were recruited. Severity of neuropathy was quantified using a vibratory perception threshold (VPT) test. The ability of perception of lower extremity was quantified by measuring obstacle-crossing success rate (OCSR), toe-obstacle clearance (TOC), and reaction time (T_R) while crossing a series of virtual obstacles with heights at 10% and 20% of the subject’s leg length. Results: No significant difference was found between groups for age and BMI. The data revealed that DPN subjects had a significantly lower OCSR compared to diabetics with no neuropathy and controls at an obstacle size of 10% of leg length (p < 0.05). DPN subjects also demonstrated longer T_R compared to other groups and for both obstacle sizes. In addition, TOC was reduced in neuropathy groups. Interestingly, a significant correlation between T_R and VPT (r = 0.5, p < 10^–3) was observed indicating a delay in reaction with increasing neuropathy severity. The delay becomes more pronounced by increasing the size of the obstacle. Using a regression model suggests that the change in T_R between obstacle sizes of 10% and 20% of leg length is the most sensitive predictor for neuropathy severity with an odds ratio of 2.70 (p = 0.02). Conclusion: The findings demonstrate proof of a concept of virtual-reality application as a promising method for objective assessment of neuropathy severity, however a further study is warranted to establish a stronger relationship between the measured parameters and neuropathy.

New virtual reality protocol for gait training in patients with multiple sclerosis

Introduction : The purpose of this research project is to evaluate the usefulness of virtual reality (VR) environments as a tool in gait training of individuals with multiple sclerosis (MS). MS is a chronic and progressive neurological disease and its clinical course can lead to severe disability. VR is a relatively new tool in the field of neuro-rehabilitation that has many advantages including the possibility to have a complete variable control management, to monitor motor level achieved by the individual through exercises, to provide challenging and engaging exercises, to run intensive training, but in a protected environment and then to provide feedback to facilitate motor learning. Methods : Ten subjects (9 females) affected by MS (mean age 40.6, range 24-60) were studied. Two patients dropped out due to transportation and family problems, these two individuals participated only to the evaluation session and never started the training and one did not participate at the last follow up. All patients had an EDSS score between 3 and 5.5 and all were treated with natalizumab or azathioprine. Clinical evaluation included the “Six minute walk test”(6MWT), the “Timed up and go test” (TUG), the “Four Square Step Test” (FSST), the “10 meter test” and the Berg Balance Scale Test (BBS). A repeated measures design was used with evaluations at 1 week pre training (pre), one week post training (post) and at one month (post_1) and three months (post_3) follow up. Kinematic and kinetic gait analysis was used to quantify gait performance using a six camera stereophotogrammetric system (Vicon T20) and the Davis marker set with two embedded force platforms (AMTI, Watertown, MA, USA). Subjects were asked to walk under usual gait conditions and during a cognitive dual task condition of serially subtracting the number three from a three digit predefined number. For the delivery of the VR training, inertial sensors (X-SENS) were used for the acquisition of orientation of the feet. Training consisted of having subjects walk on a treadmill while negotiating virtual obstacles and a virtual environment through stereoscopic glasses or on a computer screen. Training was individualized to fit the patients needs and was provided for twelve sessions (twice a week for six weeks) for a total of 45 minutes each session and consisted of three bouts of walking of ten minutes each, with breaks in between of approximately 5 minutes rest. Level of complexity and progression was increased if the individual was able to achieve success in task performance of 80%. Progression included increasing the speed of walking on the treadmill and increasing the complexity of the VR tasks (numbers of bifurcation, obstacles distracters etc). Results: No adverse events were observed during the training. After training improvements on most motor functions were observed. Endurance as measured by the distance walked over 6 minutes improved by an average of 23 meters post training and continued to show improvement at follow up (of 70.75 m from baseline). The results show an improvement of gait and balance with a decrease of fall risk confirming the relevance of rehabilitation in MS patients. Discussion: Overall the group responded positively to the VR intervention. We observed that all improvements gained were not only stable after three months follow up, but further implemented; although it is likely that the improvements gained are to be related to VR systems a control group is needed to verify our hypothesis. This is a preliminary study aimed to determine the efficacy of a VR system and the results are very encouraging to those who hope to use VR with MS patients as a form of therapy.

A remote lab for multi-robot experiments with virtual obstacles

Remote labs are increasingly being used as an effective tool for letting students practicing with real experiments, with limited effort and cost. A multi-robot setup, based on the LEGO Mindstorms technology and the Matlab environment, allowing students to experiment with real robots through the Internet, has been developed. In this paper, a novel feature of this setup is presented. The concept of virtual obstacles is introduced, and some obstacle avoidance experiments are reported in order to illustrate the main features of the proposed experimental environment.

Virtual Obstacles Based Path Planning for Mobile Robots

A virtual obstacles based path planning method for mobile robot in urban road environment is presented.It's based on both the benefits of global and local path planners.Firstly,it uses A~* algorithm to produce a global optimal path.Secondly,virtual obstacles are generated according to the global path.Finally,by fusing virtual and actual detected obstacles,the local path is planned based on the improved vector field histogram method.This method can not only fully utilize environment information to get the global optimal path,but also avoid the stochastic obstacles on the road in real-time. Practical experiments illustrate the effectiveness and robustness of this method.

Virtual Reality for Gait Training: Can It Induce Motor Learning to Enhance Complex Walking and Reduce Fall Risk in Patients With Parkinson's Disease?

Gait and cognitive disturbances are common in Parkinson's disease (PD). These deficits exacerbate fall risk and difficulties with mobility, especially during complex or dual-task walking. Traditional gait training generally fails to fully address these complex gait activities. Virtual reality (VR) incorporates principles of motor learning while delivering engaging and challenging training in complex environments. We hypothesized that VR may be applied to address the multifaceted deficits associated with fall risk in PD. Twenty patients received 18 sessions (3 per week) of progressive intensive treadmill training with virtual obstacles (TT + VR). Outcome measures included gait under usual-walking and dual-task conditions and while negotiating physical obstacles. Cognitive function and functional performance were also assessed. Patients were 67.1 ± 6.5 years and had a mean disease duration of 9.8 ± 5.6 years. Posttraining, gait speed significantly improved during usual walking, during dual task, and while negotiating overground obstacles. Dual-task gait variability decreased (ie, improved) and Trail Making Test times (parts A and B) improved. Gains in functional performance measures and retention effects, 1 month later, were also observed. To our knowledge, this is the first time that TT + VR has been used for gait training in PD. The results indicate that TT + VR is viable in PD and may significantly improve physical performance, gait during complex challenging conditions, and even certain aspects of cognitive function. These findings have important implications for understanding motor learning in the presence of PD and for treating fall risk in PD, aging, and others who share a heightened risk of falls.

Evaluation of Visual and Auditory Feedback in Virtual Obstacle Walking

This paper describes evaluation experiments for visual and auditory feedback in a virtual obstacle walking scenario. Two studies with healthy subjects were carried out using the actuated gait orthosis Lokomat. Controlled factors for the visual feedback experiment were three different perspectives and 2D/3D vision. In the auditory feedback experiment, controlled factors were rhythmic distance feedback and gradual foot clearance feedback. For the visual and auditory feedback experiments, outcome was assessed with task-specific performance parameters and questionnaires. Results for visual feedback indicate that the chosen side perspective is superior to behind and ego perspectives. It is also shown that 3D vision does not reduce the number of obstacle hits compared to 2D vision. Furthermore, it is demonstrated that adding continuous auditory feedback made subjects walk faster compared to the exclusive use of visual feedback. Subjects rated auditory distance feedback as more helpful than auditory foot clearance feedback. Therefore, we suggest using side perspective and auditory feedback on obstacle distance.

Evolutionary Univector Field-based Navigation with Collision Avoidance for Mobile Robot

This paper proposes a novel vector field navigation method by using the velocity vector of a robot to avoid obstacles in dynamic environment. Shifting vector and virtual obstacle are proposed to derive the center of repulsive field which makes the robot move away from the obstacle: The shifting vector is derived from the velocity vector of the robot and the obstacle and the virtual obstacle is made by adding the shifting vector to the real obstacle. By considering the velocity vector of an obstacle with a shifting vector and a virtual obstacle, the robot can avoid not only stationary obstacles but also dynamic obstacles, where the fields are optimized by evolutionary programming. The performance of proposed method is demonstrated by simulations and experiments in robot soccer system.

Obstacle avoidance during walking in real and virtual environments

Immersive virtual environments are a promising research tool for the study of perception and action, on the assumption that visual--motor behavior in virtual and real environments is essentially similar. We investigated this issue for locomotor behavior and tested the generality of Fajen and Warren's [2003] steering dynamics model. Participants walked to a stationary goal while avoiding a stationary obstacle in matched physical and virtual environments. There were small, but reliable, differences in locomotor paths, with a larger maximum deviation (Δ = 0.16 m), larger obstacle clearance (Δ = 0.16 m), and slower walking speed (Δ = 0.13 m/s) in the virtual environment. Separate model fits closely captured the mean virtual and physical paths (R 2 &gt; 0.98). Simulations implied that the path differences are not because of walking speed or a 50% distance compression in virtual environments, but might be a result of greater uncertainty about the egocentric location of virtual obstacles. On the other hand, paths had similar shapes in the two environments with no difference in median curvature and could be modeled with a single set of parameter values (R 2 &gt; 0.95). Fajen and Warren's original parameters successfully generalized to new virtual and physical object configurations (R 2 &gt; 0.95). These results justify the use of virtual environments to study locomotor behavior.

High school graduate refines gyromouse interface for virtual reality

Matt Duncan was a graduating senior at Yorktown High School in Arlington Virginia when he visited our university for a three-week for-credit internship. The goal was for him to learn about 3D graphic design and interaction design while helping us develop our Virtual Reality (VR) technology. The result was beneficial for everyone. He learned how to build virtual environments and to compare and refine VR navigation and selection techniques though collaboration with users. We got a virtual obstacle course for VR navigation training and a very intuitive interaction for VR navigation with the Gyromouse.

Determinants guiding alternate foot placement selection and the behavioral responses are similar when avoiding a real or a virtual obstacle

In this study we validate the use of a virtual planar obstacle paradigm to study the avoidance of a real obstacle, such as a hole, during locomotion. Also we further validate the economy determinant implicated with the minimization of foot displacement from its normal landing position during alternate foot placement. Participants were asked to perform two blocks of trials: real (a real hole was embedded in the pathway and participants were requested to avoid stepping into it) and virtual (a virtual planar obstacle was displayed on the screen of a liquid crystal display monitor). Trunk and feet kinematics were monitored, as well as electromyography (EMG) activity of 14 muscles of both lower limbs and trunk. The results of this study showed that the dominant choice for each obstacle investigated was not different between the real and virtual conditions. In addition, dynamic stability, economy and forward progression determinants guiding alternate foot placement were similarly satisfied. Thus the use of virtual planar obstacle in adaptive locomotion study is appropriate. EMG data were used to compute an index relating the changes in muscle activity relative to the normal walking profile. This EMG index was significantly and positively correlated with the amount of foot displacement for the adaptive step. The fact that the dominant choice resulted in minimum foot displacement from its normal landing spot combined with minimal changes in muscle activity validates conclusively the economy determinant.

The beam analysis algorithm for path planning for redundant manipulators

An algorithm for path planning for redundant manipulators is presented in this paper. The algorithm uses harmonic potential fields defined globally in W-space (work space) for both path planning and obstacle avoidance. Although paths generated by harmonic potential fields are collision free for point robots, this is not always the case for manipulators when especially tight manoeuvring is required. To enhance collision avoidance ability of redundant manipulators, the beam analysis algorithm is proposed. The algorithm sends beams along the path generated for point robots to determine virtual obstacle points where collision with obstacle is likely to occur. The potential field is then regenerated to include these virtual obstacle points. Besides, the interaction between manipulator links and the potential field is accomplished by the control points situated on only proximal ends of the links. The virtual obstacle points and selected control points allow the manipulator to achieve tight manoeuvring in W-spaces cluttered with many obstacles. The improvement in performance is also clearly indicated by a benchmark scheme that compares the algorithms by means of the complexity of the environment with respect to link lengths of redundant manipulators. Furthermore, the beam analysis algorithm readily produces safer paths for mobile robots, which does not suffer too far or too close problems. Examples are included to demonstrate these features of the algorithm.

Virtual Enterprise Networks in Europe - Economic Opportunities and Legal Challenges

Virtual enterprises (VEs) are a result of e-business which emerged as a reaction to fast evolving market trends. We discuss organizational as well as legal implications. These are of importance for a proper functioning of this new form of business partnership. This paper will show the needs for virtual enterprising and obstacles to the future development of which the issue of trust is one of the most important. Especially consumers' trust could be enhanced by a clear regulation of VE's liability which has so far not been covered in the literature. We will therefore present several models on possible liability rules and a concept which meets the requirements of providing adequate economic incentives for the participating companies and being easy to handle by consumers as a policy recommendation for future harmonization of Member States' National Law.

Stepping over obstacles to improve walking in individuals with poststroke hemiplegia

For this study, we evaluated two training interventions for improving gait parameters in individuals with poststroke hemiplegia using a training methodology that required them to step over objects. Gait velocity, step length, ability to step over obstacles, and walking endurance were compared before and after 2 weeks of training and 2 weeks after cessation of training. Twenty subjects with poststroke hemiplegia completed six intervention sessions in which they were asked to step over either virtual objects while walking on a motorized treadmill or real foam objects on a 10 m walkway. With the virtual object training, if either foot collided with the virtual object, a tone sounded and a vibrotactile stimulus was applied to the colliding foot. All subjects tolerated the training sessions well, and no incidences of falling or undue cardiovascular responses occurred. The virtual obstacle training generated greater improvements in gait velocity compared with real training (20.5% vs. 12.2% improvement) during the fast walk test (p < 0.01). Improvements in gait velocity for both training methods were similar in the self-selected walk test (33.3% vs. 34.7% improvement). Overall, subjects showed clinically meaningful changes in gait velocity, stride length, walking endurance, and obstacle clearance capacity as a result of either training method. These changes persisted for 2 weeks posttraining. The inclusion of enhanced safety and visual augmentation may be responsible for the effectiveness of the virtual object intervention. These results demonstrate preliminary evidence for clinical effectiveness of obstacle training for improving gait velocity poststroke. In addition, these results provide evidence for enhanced clinical performance with virtual obstacle training.

A new technique to escape local minimum in artificial potential field based path planning

The artificial potential field (APF) methods provide simple and efficient motion planners for practical purposes. However, these methods have a local minimum problem, which can trap an object before reaching its goal. The local minimum problem is sometimes inevitable when an object moves in unknown environments, because the object cannot predict local minima before it detects obstacles forming the local minima. The avoidance of local minima has been an active research topic in the potential field based path planing. In this study, we propose a new concept using a virtual obstacle to escape local minima that occur in local path planning. A virtual obstacle is located around local minima to repel an object from local minima. We also propose the discrete modeling method for the modeling of arbitrary shaped objects used in this approach. This modeling method is adaptable for real-time path planning because it is reliable and provides lower complexity.

Non-smooth environment modeling and global path planning for mobile robots

An Approximate Voronoi Boundary Network is constructed as the environmental model by way of enlarging the obstacle raster. The connectivity of the path network under complex environment is ensured through building the second order Approximate Voronoi Boundary Network after adding virtual obstacles at joint-close grids. This method embodies the network structure of the free area of environment with less nodes, so the complexity of path planning problem is reduced largely. An optimized path for mobile robot under complex environment is obtained through the Genetic Algorithm based on the elitist rule and re-optimized by using the path-tightening method. Since the elitist one has the only authority of crossover, the management of one group becomes simple, which makes for obtaining the optimized path quickly. The Approximate Voronoi Boundary Network has a good tolerance to the imprecise a priori information and the noises of sensors under complex environment. Especially it is robust in dealing with the local or partial changes, so a small quantity of dynamic obstacles is difficult to alter the overall character of its connectivity, which means that it can also be adopted in dynamic environment by fusing the local path planning.