Obstacle Distance Research Articles

Budgerigar flight in a varying environment: flight at distinct speeds?

How do flying birds respond to changing environments? The behaviour of budgerigars, Melopsittacus undulatus, was filmed as they flew through a tapered tunnel. Unlike flying insects-which vary their speed progressively and continuously by holding constant the optic flow induced by the walls-the birds showed a tendency to fly at only two distinct, fixed speeds. They switched between a high speed in the wider section of the tunnel, and a low speed in the narrower section. The transition between the two speeds was abrupt, and anticipatory. The high speed was close to the energy-efficient, outdoor cruising speed for these birds, while the low speed was approximately half this value. This is the first observation of the existence of two distinct, preferred flight speeds in birds. A dual-speed flight strategy may be beneficial for birds that fly in varying environments, with the high speed set at an energy-efficient value for flight through open spaces, and the low speed suited to safe manoeuvring in a cluttered environment. The constancy of flight speed within each regime enables the distances of obstacles and landmarks to be directly calibrated in terms of optic flow, thus facilitating simple and efficient guidance of flight through changing environments.

Mobile robot navigation in unknown static environments using ANFIS controller

Summary Navigation and obstacle avoidance are the most important task for any mobile robots. This article presents the Adaptive Neuro-Fuzzy Inference System (ANFIS) controller for mobile robot navigation and obstacle avoidance in the unknown static environments. The different sensors such as ultrasonic range finder sensor and sharp infrared range sensor are used to detect the forward obstacles in the environments. The inputs of the ANFIS controller are obstacle distances obtained from the sensors, and the controller output is a robot steering angle. The primary objective of the present work is to use ANFIS controller to guide the mobile robot in the given environments. Computer simulations are conducted through MATLAB software and implemented in real time by using C/C++ language running Arduino microcontroller based mobile robot. Moreover, the successful experimental results on the actual mobile robot demonstrate the effectiveness and efficiency of the proposed controller.

A gradient-based path optimization method for motion planning

Most algorithms in probabilistic sampling-based path planning compute collision-free paths made of straight line segments lying in the configuration space. Due to the randomness of sampling, the paths make detours that need to be optimized. The contribution of this paper is to propose a basic gradient-based algorithm that transforms a polygonal collision-free path into a shorter one. While requiring only collision checking, and not any time-consuming obstacle distance computation nor geometry simplification, we constrain only part of the configuration variables that may cause a collision, and not entire configurations. Thus, parasite motions that are not useful for the problem resolution are reduced without any assumption. Experimental results include navigation and manipulation tasks, eg a manipulator arm-filling boxes and a PR2 robot working in a kitchen environment. Comparisons with a random shortcut optimizer and a partial shortcut have also been studied.

Design of capacitive micromachined ultrasonic transducer (CMUT) linear array for underwater imaging

Purpose – The purpose of this paper was to develop a novel capacitive micromachined ultrasonic transducer (CMUT) reception and transmission linear array for underwater imaging at 400 kHz. Compared with traditional CMUTs, the developed transducer array offers higher electromechanical coupling coefficient and higher directivity performance. Design/methodology/approach – The configuration of the newly developed CMUT reception and transmission array was determined by the authors’ previous research into new element structures with patterned top electrodes and into directivity simulation analysis. Using the Si-Silicon on insulator (Si-SOI) bonding technique and the principle of acoustic impedance matching, the CMUT array was fabricated and packaged. In addition, underwater imaging system design and testing based on the packaged CMUT 1 × 16 array were completed. Findings – The simulation results showed that the optimized CMUT array configuration was selected. Furthermore, the designed configuration of the CMUT 1 × 16 linear array was good enough to guarantee high angular resolution. The underwater experiments were conducted to demonstrate that this CMUT array can be of great benefit in imaging applications. Practical implications – Based on our research, the CMUT linear array has good directivity and good impedance matching with water and can be used for obstacle avoidance, distance measurement and imaging underwater. Originality/value – This research provides a basis for CMUT directivity theory and array design. CMUT array presented in this paper has good directivity and has been applied in the underwater imaging, resulting in a huge market potential in underwater detection systems.

移動ロボットを用いた遠隔操作と自律動作の行動調停に関する研究

This paper describes the integration system of teleoperation and autonomous operation for a mobile robot. We developed the four-wheeled mobile robot that has several sensors capable of recognizing environments. The teleoperation is controlled by a tablet device. The autonomous operation is controlled by the fuzzy control based on GPS and a laser range finder. The integration system is composed of an update formula of control weights for obstacle distances and the weighted average calculation. In obstacle avoidance experiments, the effectiveness of the integration system is confirmed.

A new hybrid intelligent path planner for mobile robot navigation based on adaptive neuro-fuzzy inference system

In this paper, a new intelligent motion planning approach to mobile robot navigation is addressed. Adaptive neuro-fuzzy inference system (ANFIS) is a well-known hybrid neuro-fuzzy structure for modelling the engineering system. It has also taken the advantages of both learning ability of neural network and the reasoning ability of the fuzzy inference system. In this navigational model, different sensor-extracted information, such as front obstacle distance, right obstacle distance, left obstacle distance, heading angle, left wheel velocity and right wheel velocity, are given input to the ANFIS controller and output from the controller is steering angle for the robot. Based on the output information, the robot moves safely in an unstructured environment populated by variety of static obstacles. Using ANFIS tool box, the obtained mean of squared error for the training dataset in the current paper is 0.0021. Finally, the simulation results are verified with real-time experimental results using Khepra-III mobile robot to show the feasibility and effectiveness of the proposed navigational algorithm.

IWO-based adaptive neuro-fuzzy controller for mobile robot navigation in cluttered environments

In this paper, a new hybrid intelligent motion planning approach to mobile robot navigation is presented. In this new hybrid methodology, the invasive weed optimization (IWO) algorithm is used for training the premise parameters, and the least square estimation (LSE) method is used for training the consequent part of the adaptive neuro-fuzzy inference system (ANFIS). In this proposed navigational model, different kinds of sensor-extracted information, such as front obstacle distance (FOD), right obstacle distance (ROD), left obstacle distance (LOD), heading angle (HA), left wheel velocity (LWV), and right wheel velocity (RWV), are given input to the hybrid controller, in order to calculate the suitable steering angle (SA) for the robot. Using the IWO algorithm, the obtained root mean of squared error (RMSE) for the training data set in the ANFIS is 0.0013. The simulation results are verified by the real-time experimental results, using the Khepera III mobile robot to show the versatility and effectiveness of the proposed hybrid navigational algorithm. The results obtained using the proposed hybrid algorithm are validated by comparison with the results from other intelligent algorithms. Finally, it is proved that the proposed hybrid navigational controller can be implemented in the robot for navigation in any complex environments.

Improving Mobility Performance in Low Vision With a Distance-Based Representation of the Visual Scene.

Severe visual impairment can have a profound impact on personal independence through its effect on mobility. We investigated whether the mobility of people with vision low enough to be registered as blind could be improved by presenting the visual environment in a distance-based manner for easier detection of obstacles. We accomplished this by developing a pair of "residual vision glasses" (RVGs) that use a head-mounted depth camera and displays to present information about the distance of obstacles to the wearer as brightness, such that obstacles closer to the wearer are represented more brightly. We assessed the impact of the RVGs on the mobility performance of visually impaired participants during the completion of a set of obstacle courses. Participant position was monitored continuously, which enabled us to capture the temporal dynamics of mobility performance. This allowed us to find correlates of obstacle detection and hesitations in walking behavior, in addition to the more commonly used measures of trial completion time and number of collisions. All participants were able to use the smart glasses to navigate the course, and mobility performance improved for those visually impaired participants with the worst prior mobility performance. However, walking speed was slower and hesitations increased with the altered visual representation. A depth-based representation of the visual environment may offer low vision patients improvements in independent mobility. It is important for further work to explore whether practice can overcome the reductions in speed and increased hesitation that were observed in our trial.

Identification of Vibrotactile Patterns Encoding Obstacle Distance Information.

Delivering distance information of nearby obstacles from sensors embedded in a white cane-in addition to the intrinsic mechanical feedback from the cane-can aid the visually impaired in ambulating independently. Haptics is a common modality for conveying such information to cane users, typically in the form of vibrotactile signals. In this context, we investigated the effect of tactile rendering methods, tactile feedback configurations and directions of tactile flow on the identification of obstacle distance. Three tactile rendering methods with temporal variation only, spatio-temporal variation and spatial/temporal/intensity variation were investigated for two vibration feedback configurations. Results showed a significant interaction between tactile rendering method and feedback configuration. Spatio-temporal variation generally resulted in high correct identification rates for both feedback configurations. In the case of the four-finger vibration, tactile rendering with spatial/temporal/intensity variation also resulted in high distance identification rate. Further, participants expressed their preference for the four-finger vibration over the single-finger vibration in a survey. Both preferred rendering methods with spatio-temporal variation and spatial/temporal/intensity variation for the four-finger vibration could convey obstacle distance information with low workload. Overall, the presented findings provide valuable insights and guidance for the design of haptic displays for electronic travel aids for the visually impaired.

Methane–air explosion characteristics with different obstacle configurations

To investigate the flame and overpressure characteristics of methane–air explosion with different obstacle configurations, an experimental study has been conducted, taking account of the number of obstacles, obstacle distance from ignition source, and stream-wise and cross-wise obstacle positions. The results show that the flame speed and peak overpressure increase with the increasing number of obstacles, while the time to reach the peak is not fully determined by it. And the configuration having the farthest obstacle produces a higher overpressure and takes a longer time to reach the peak, but a slower flame propagation speed is obtained. Similar explosion characteristics are also observed in the configurations with two obstacles fixed at different stream-wise positions. Furthermore, the experimental results demonstrate that the peak overpressures and flame speeds in configurations with central or staggered obstacles are relatively higher, which should to be avoided in practical processes to minimize the risk associated with methane–air explosion.

Path Generation for Robot Navigation using a Single Camera

The work focus on providing a path in an environment for a robot for its ease of movement, detecting and avoiding obstacles in an environment using a single camera and a laser source. Robot moves by identifying free space in floor. Wherever floor is visible and free, it moves. Novel method for floor segmentation has been used. Laser source emits light that falls on obstacle if any, and based on position of laser light on obstacle in the image and distance of obstacle from robot, robot change its direction with different angle and continues to move. This movement information is stored in text file which is used to create map of the environment. Absence of laser light with different floor mark will be treated as hole in the floor and will be skipped.

Electronic Bracelet and Vision-Enabled Waist-Belt for Mobility of Visually Impaired People

A wearable assistive system is proposed to improve mobility of visually impaired people (subjects). This system has been implemented in the shape of a bracelet and waist-belt in order to increase its wearable convenience and cosmetic acceptability. A camera and an ultrasonic sensor are attached to a customized waist-belt and bracelet, respectively. The proposed modular system will act as a complementary aid along with a white cane. Its vision-enabled waist-belt module detects the path and distribution of obstacles on the path. This module conveys the required information to a subject via a mono earphone by activating relevant spoken messages. The electronic bracelet module assists the subject to verify this information and to perceive distance of obstacles along with their locations. The proposed complementary system provides an improved understanding of the surrounding environment with less cognitive and perceptual efforts as compared to a white cane alone. This system was subjected to clinical evaluations with 15 totally blind subjects. Results of usability experiments demonstrated effectiveness of the system as a mobility aid. Amongst the participated subjects, 93.33% expressed satisfaction with the information content of this system, 86.66% subjects comprehended its operational convenience, and 80% appreciated the comfort of the system.

A New Intelligent Motion Planning for Mobile Robot Navigation using Multiple Adaptive Neuro-Fuzzy Inference System

Nowadays intelligent tools such as fuzzy inference system (FIS), artific ial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are mainly considered as effective and suitable methods for modeling an engineering system. This paper presents a new hybrid technique based on the combination of fuzzy inference system and artificial neural network for addressing navigational problem of autonomous mobile robot. First we developed an adaptive fuzzy controller with four input parameters, two output parameters and three parameters each. Afterwards each adaptive fuzzy controller acts as a single takagi-sugeno type fuzzy inference system, where inputs are front obstacle distance (FOD), left obstacle distance (LOD), right obstacle distance (ROD) (from robot), heading angle (HA) (angle to target) and output corresponds to the wheel velocities ( Left wheel and right wheel) for the mobile robot. The effectiveness, feasibility and robustness of the prop osed navigational controller have been demonstrated by means of simulation experiments. The real time experimental results were verifie d with simulation experiments, showing that the proposed navigational algorithm consistently performs better results to navigate the mo bile robot safely in a completely or partially unknown environment.

Neural Network Navigation Technique for Unmanned Vehicle

Using a neural network (ANN) for the brain, we want a vehicle to drive by itself avoiding obstacles. We accomplish this by choosing the appropriate inputs/outputs and by carefully training the ANN. We feed the network with distances of the closest obstacles around the vehicle to imitate what a human driver would see. The output is the acceleration and steering of the vehicle. We also need to train the network with a set of strategic input-output. The result is impressive, for a couple of neurons! The unmanned vehicle (UV) drives around avoiding obstacles, but some improvement or modification can be done to make this software work for a specific purpose.

Navigation of autonomous mobile robot using adaptive network based fuzzy inference system

Intelligent soft computing techniques such as fuzzy inference system (FIS), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are proven to be efficient and suitable when applied to a variety of engineering systems. The hallmark of this paper investigates the application of an adaptive neuro-fuzzy inference system (ANFIS) to path generation and obstacle avoidance for an autonomous mobile robot in a real world environment. ANFIS has also taken the advantages of both learning capability of artificial neural network and reasoning ability of fuzzy inference system. In this present design model different sensor based information such as front obstacle distance (FOD), right obstacle distance (ROD), left obstacle distance (LOD) and target angle (TA) are given input to the adaptive fuzzy controller and output from the controller is steering angle (SA) for mobile robot. Using ANFIS tool box, the obtained mean of squared error (MSE) for training data set in the current paper is 0.031. The real time experimental results also verified with simulation results, showing that ANFIS consistently perform better results to navigate the mobile robot safely in a terrain populated by variety obstacles.

A novel artificial immune algorithm for spatial clustering with obstacle constraint and its applications.

An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE) algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

Automatic Train Protection Simulation for Radio-Based Train Control System

Rail transport is facing major challenges today. On one hand, it must meet the needs of citizens for greater mobility while, on the other, it must provide a valid alternative to other modes of transport against a backdrop of rising fuel prices and the increasing importance of the impact of transport on the environment. In this context, rail transport must be ever more efficient. In this project we are going to prevent the train collision using MIWI communication. Transmitter will send a data (track1) from transmitter side and receiver receives the same data at receiver side. If the receiver is in another track the engine driver will send a data (track2) through transmitter and received by the receiver. If both the trains in the same track means, both the transmitters and receivers will send the same track no and immediately buzzer will give alert on both the sides. Thus the train collision is prevented. There is also a PIR sensor which is fixed in the train, to give electric supply when there is a human being is sitting inside the train. There is also an ultrasonic sensor which is attached to the train which intimates the distance of the obstacle

Creating Obstacle Courses for Raft Proteins - How Micropatterning Can Help Decipher Plasma Membrane Organization

According to prevailing theory, sterol- and sphingolipid enriched nanodomains exist in the mammalian plasma membrane but are too small and dynamic to allow for proper characterization. Attempts to artificially enhance putative tendencies in the plasma membrane to create optically resolvable phase separation have yielded new model systems like Giant Plasma Membrane Vesicles, bridging the gap between synthetic lipid bilayers and live cell membranes.In this work, we take those approaches one step further and attempt to create large scale phase separation in a live cell situation. To this end, we use a micropatterning technique to artificially create regions in the PM of live cells where we use a model raft protein glycosylphosphatidylinositol (GPI-GFP) is immobilized and highly enriched (via surface-immobilzed antibodies) at different densities to monitor the effects on plasma membrane organization and properties.Our key findings are: 1) Within patterned regions, we can immobilize and enrich GPI-GFP up to densities of 10,000 proteins/µm2 corresponding to average center-center distances of 9nm. 2) We do not observe colocalization of raft markers (CD59, cholera toxin) within GPI-GFP patterns. 2) The diffusion of CD59 is unhindered within patterns up to GPI-GFP obstacle distances of ∼17nm. At even small distances, the diffusion coefficient of CD59 decreases until a threshold is reached at ∼11nm. 3) A fluorescent cholesterol derivative diffuses virtually unhindered within patterns even at GPI-GFP distances of 9-10nm. Considering the size of the GPI-GFP obstacles and Fab-labeled CD59, the slowing of diffusion within patterns can probably be explained by steric hindrance alone, arguing against the association of either GPI-GFP or CD59 in nanodomains. We further find no evidence for the formation of a continuous raft phase or even an enrichment of a different, raft-like membrane phase within patterns.

The balance between aesthetics and performance in building-integrated photovoltaics in the tropics

This paper aims at investigating if the balance between aesthetics and performance in building-integrated photovoltaic (BIPV) systems is possible to be achieved in the tropics. To accomplish this objective, three BIPV systems located in Singapore with photovoltaic (PV) systems playing an aesthetically appealing role in their architecture were analysed in detail for a 1-year period. The systems were analysed regarding the available solar irradiation, the shading profiles and the resulting yield and performance ratio (PR) in order to compare the performance of different subsystems with variable architectural characteristics and string configurations. All systems are partially shaded in the early morning or late afternoon, a common situation inherent to BIPV systems. Results show that even with a theoretical non-optimal combination of azimuthal deviations and tilt angles, some PV systems show better performances in terms of yield and PR than those which are installed at more ideal conditions. The high ratio of diffuse irradiation in Singapore, the distance of shading obstacles and times when shading occurs and the subsystem and string configurations strongly influence the systems performance results. With the declining costs of PV systems, BIPV can offer attractive solutions with high integration appeal, architectural sophistication and the promotion of sustainable energy supply. In the tropics, rooftop BIPV systems can perform with relatively small losses and be aesthetically appealing when compared with optimally tilted and oriented PV generators. Copyright © 2013 John Wiley & Sons, Ltd.

The Design of Hopping Angle Control by Using PID and LQR Techniques

It is very difficult for hopping robots to follow the trajectory without controlling hopping angle. A hopping angle controller is designed for combustion piston type hopping robot to adjust the angle of hop which is required to achieve a desired distance or height. So, the controller adds functionality to hopping robot for altering the hopping angle during operation according to obstacle height and obstacle distance. A proportional Integrated Derivative (PID) and Linear Quadratic Regulator (LQR) are designed and compared for adjusting hopping angle by using MATLAB / SIMULINK environment. As result, both controllers are capable to control hopping angle but PID gives better performance. An implementation of PID controller for the hopping angle control is given by using a DC motor. The experiment also carried out on prototype by using PID controller and found satisfactory results.