Search results

The purpose of this paper is to describe a compact wheelchair, which has two 3-degrees of freedom (DOF) legs and a 1-DOF base (the total DOF of the leg system is 7) for stair-climbing, and wheels for flat surface driving.

The proposed wheelchair climbs stairs using the two 3-DOF legs with boomerang-shaped feet. The leg mechanisms are folded into the compact wheelchair body when the wheelchair moves over flat surfaces. The authors also propose a simple estimation method of stair shape using laser distance sensors, and a dual motor driving system to increase joint power.

The proposed wheelchair can climb arbitrary height and width stairs by itself, even when they are slightly curved. During climbing, the trajectory of the seat position is linear to guarantee the comfort of rider, and the wheelchair always keeps a stable condition to ensure the stability in an emergency stop.

The wheelchair mechanism with foldable legs and driving wheels enables smooth stair climbing, efficient flat surface driving and additional useful motions such as standing and tilting.

The purpose of this study is to propose a novel plane-based mapping method for legged-robot navigation in a stairway environment.

The approach implemented in this study estimates a plane for each step of a stairway using a weighted average of sensor measurements and predictions. It segments planes from point cloud data via random sample consensus (RANSAC). The prediction uses the regular structure of a stairway. When estimating a plane, the algorithm considers the errors introduced by the distance sensor and RANSAC, in addition to stairstep irregularities, by using covariance matrices. The plane coefficients are managed separately with the data structure suggested in this study. In addition, this data structure allows the algorithm to store the information of each stairstep as a single entity.

In the case of a stairway environment, the accuracy delivered by the proposed algorithm was higher than those delivered by traditional mapping methods. The hardware experiment verified the accuracy and applicability of the algorithm.

The proposed algorithm provides accurate stairway-environment mapping and detailed specifications of each stairstep. Using this information, a legged robot can navigate and plan its motion in a stairway environment more efficiently.

The purpose of this paper is to design and test effective indoor navigation solutions for visually impaired people in situations where GPS, bluetooth or Wi-Fi signals are unavailable. The authors use the inertial measurement units (IMU), the compass and the barometer of a smart phone.

The authors have used commercial Android smart phones with IMU, compass and barometer to record a path and to give navigation instructions in an adapted way using a mobility-specific vocabulary. The method proposed is to save paths taking into account different indoor waypoints such as the stairs (change from one floor to another) and the change of direction of the trajectory of the path (e.g. one-fourth turn right or left), recording data from the IMU sensor’s, compass and barometer of the smart phone. Having this information and the characteristics of the each segment (distance, azimuth to the north and pressure) of the path, it is possible to provide functional navigation guidance to the visually impaired subject. Three different visually impaired people (one partially sighted and two fully blind) and three sighted people have tested the paths. The efficiency of the navigation is analyzed in terms of distance and time using the comparison between blind and sighted people.

The main finding is that it is possible to guide visually impaired people some hundreds of meters just using the sensors of a smart phone under certain conditions: the visually impaired person has to understand the guidance instructions and respect some strategies (e.g. not to walk diagonally across vast spaces). Additionally it is observed that the visually impaired participants walked distances, which are not much different to the optimal values. On the other hand; because of their hesitations using their white cane to find free paths, they take in some cases 50 percent more time to arrive (for a few minutes path, this time is not critical and even more efficient than looking for a guide). One thing to highlight is that even with this hesitation, the subjects arrived to the final destination.

This paper demonstrates how an IMU coupled to a compass and a barometer from a Smart Phone employing a spoken mobility language (e.g. next corridor to the left; at the end of the stairs turn right, turn left, etc.) can guide visually impaired people inside buildings.

Lower-limb exoskeleton systems enable people with spinal cord injury to regain some degree of locomotion ability, as the expected motion curve needs to adapt with changing scenarios, i.e. stair heights, distance to the stairs. The authors’ approach enables exoskeleton systems to adapt to different scenarios in stair ascent task safely.

In this paper, the authors learn the locomotion from predefined trajectories and walk upstairs by re-planning the trajectories according to external forces posed on exoskeleton systems. Moreover, instead of using complex sensors as inputs for re-planning in real-time, the approach can obtain forces acting on exoskeleton through dynamic model of human-exoskeleton system learned by an online machine learning approach without accurate parameters.

The proposed approach is validated in both simulation environment and a real walking assistance exoskeleton system. Experimental results prove that the proposed approach achieves better performance than the traditional predefined gait approach.

First, the approach obtain the external forces by a learned dynamic model of human-exoskeleton system, which reduces the cost of exoskeletons and avoids the heavy task of translating sensor input into actuator output. Second, the approach enables exoskeleton accomplish stair ascent task safely in different scenarios.

This study aims to investigate if smartphone sensors can be used in an unmanned aerial vehicle (UAV) localization system. With the development of technology, smartphones have been tentatively used in micro-UAVs due to their lightweight, inexpensiveness and flexibility. In this study, a Samsung Galaxy S3 smartphone is selected as an on-board sensor platform for UAV localization in Global Positioning System (GPS)-denied environments and two main issues are investigated: Are the phone sensors appropriate for UAV localization? If yes, what are the boundary conditions of employing them?

Efficient accuracy estimation methodologies for the phone sensors are proposed without using any expensive instruments. Using these methods, one can estimate his phone sensors accuracy at any time without special instruments. Then, a visual-inertial odometry scheme is introduced to evaluate the phone sensors-based path estimation performance.

Boundary conditions of using smartphone in a UAV navigation system are found. Both indoor and outdoor localization experiments are carried out and experimental results validate the effectiveness of the boundary conditions and the corresponding implemented scheme.

With the phone as a payload, UAVs can be further realized in smaller scale at lower cost, which will be used widely in the field of industrial robots.

The purpose of this paper is to develop an online smoothing zero-velocity-update (ZUPT) method that helps achieve smooth estimation of human foot motion for the ZUPT-aided inertial pedestrian navigation system.

The smoothing ZUPT is based on a Rauch–Tung–Striebel (RTS) smoother, using a six-state Kalman filter (KF) as the forward filter. The KF acts as an indirect filter, which allows the sensor measurement error and position error to be excluded from the error state vector, so as to reduce the modeling error and computational cost. A threshold-based strategy is exploited to verify the detected ZUPT periods, with the threshold parameter determined by a clustering algorithm. A quantitative index is proposed to give a smoothness estimate of the position data.

Experimental results show that the proposed method can improve the smoothness, robustness, efficiency and accuracy of pedestrian navigation.

Because of the chosen smoothing algorithm, a delay no longer than one gait cycle is introduced. Therefore, the proposed method is suitable for applications with soft real-time constraints.

The paper includes implications for the smooth estimation of most types of pedal locomotion that are achieved by legged motion, by using a sole foot-mounted commercial-grade inertial sensor.

This paper helps realize smooth transitions between swing and stance phases, helps enable continuous correction of navigation errors during the whole gait cycle, helps achieve robust detection of gait phases and, more importantly, requires lower computational cost.

The purpose of this paper is to demonstrate that significant surface finish improvements can be accomplished in stereolithography (SL) fabricated parts by applying a new process planning method based on parameter estimation (PE).

PE is a method that finds a set of parameter values that minimize a measure of deviation. In this work, the measure of deviation is the difference between the exposure received by points along down‐facing surfaces and the SL resin's critical exposure.

The surface finish of down‐facing surfaces can be improved by a factor of 2‐9, depending upon the surface angle, compared with parts prepared using commercially available software. Surface finishes less than 1 μm Ra have been demonstrated on a SLA‐250/50 machine.

Only down‐facing surfaces can have their surface finish improved using this method.

Common form errors known as “stair‐stepping” can be diminished on parts fabricated using SL.

The usage of PE methods for process planning is a new approach.

This study aims to design a new low-cost localization platform for estimating the location and orientation of a pedestrian in a building. The micro-electro-mechanical systems (MEMS) sensor error compensation and the algorithm were improved to realize the localization and altitude accuracy.

The platform hardware was designed with common low-performance and inexpensive MEMS sensors, and with a barometric altimeter employed to augment altitude measurement. The inertial navigation system (INS) – extended Kalman filter (EKF) – zero-velocity updating (ZUPT) (INS-EKF-ZUPT [IEZ])-extended methods and pedestrian dead reckoning (PDR) (IEZ + PDR) algorithm were modified and improved with altitude determined by acceleration integration height and pressure altitude. The “AND” logic with acceleration and angular rate data were presented to update the stance phases.

The new platform was tested in real three-dimensional (3D) in-building scenarios, achieved with position errors below 0.5 m for 50-m-long route in corridor and below 0.1 m on stairs. The algorithm is robust enough for both the walking motion and the fast dynamic motion.

The paper presents a new self-developed, integrated platform. The IEZ-extended methods, the modified PDR (IEZ + PDR) algorithm and “AND” logic with acceleration and angular rate data can improve the high localization and altitude accuracy. It is a great support for the increasing 3D location demand in indoor cases for universal application with ordinary sensors.

This paper aims to provide a theoretical principle for the stability control of robot climbing stairs, autonomously based on human–robot interaction. Through this research, tracked mobile robots with human-robot interaction will be extensively used in rescue in disaster, exploration on planetary, fighting in battle, and searching for survivors in collapsed buildings.

This paper introduces the tracked mobile robot, based on human–robot interaction, and its six moving postures. The dynamic process of climbing stairs is analyzed, and the dynamic model of the robot is proposed. The dynamic stability criterion is derived when the tracked mobile robot contacts the stairs steps in one, two and more points. A further conduction of simulation on the relationship of the traction force and bearing force vs the velocity and acceleration in the three cases was carried out.

This paper explains that the tracked mobile robot, based on human–robot interaction, can stably climb stairs so long as the velocity and acceleration satisfy the dynamic stability criterion as noted above. In addition, the experiment tests the correctness of dynamic stability analysis when the tracked mobile robot contacts the stair steps in one, two or more points.

This paper provides the mechanical structure and working principle of the tracked mobile robot based on human–robot interaction and proposes an identification method of dynamic stability criterion when the robot contacts the stairs steps in one, two and more points.

Analyzing different scenarios at the design stage of construction projects has always been a challenging task. One of the main parameters that helps owners in making better decisions in designing their buildings is to look after the cost perspective on different design scenarios. Thus, this study aims to propose a semi-automated BIM-based cost estimation approach that enables practitioners to estimate the cost of projects based on different design scenarios by an accurate and agile system.

This study proposes an integrated framework, through which the cost estimation standard of Iran (FehrestBaha) is linked to the materials quantity take-offs (QTO) from BIM models. The performance of the system is based on connecting the classification standards of UniFormat and MasterFormat to the cost estimation standard of FehrestBaha. A BIM-based extension in the Revit environment is developed to automate the cost estimation process.

To evaluate the efficiency of the proposed approach in cost estimation, it is implemented to estimate the cost of the architectural discipline in a real construction project. The results indicate that the proposed BIM-based approach estimated the cost of the architectural discipline with an acceptable level of accuracy.

The proposed approach could be used by practitioners to have an agile and accurate BIM-based cost estimation of different scenarios during design process. The semi-automated system considerably reduces the time of cost estimation in comparison to the traditional manual approaches, particularly in complex structures. Owners are able to easily trace changes in project cost according to any changes in components and materials of the BIM model. Furthermore, the proposed approach provides a practical roadmap for BIM-based cost estimation based on cost estimation standards in different countries.

Unlike the traditional manual cost estimation approaches, the proposed BIM-based approach is not highly dependent on the knowledge of experienced estimators, which therefore facilitates its implementation. Furthermore, automating both QTO process and the required calculations in this approach increases the accuracy of cost estimation while decreasing the probability of human errors or omission occurrence.