Collision Avoidance Task Research Articles

Operability Evaluation of Pleasure Boats Based on Usability as Addressed by ISO 9241-11

This paper proposes an evaluation method for operability of pleasure boats in order to develop an electronic control steering system of those boats. Based on usability as addressed by ISO 9241-11, some evaluation criteria such as effectiveness and efficiency are defined for a task of collision avoidance and course resuming. For safety and repeatability, the simulation with a simplified ship simulator, which is composed a manual hydraulic steering system as hardware in HILS, is performed instead of experiments. As a result of the simulation, it is found that the operability of the manual hydraulic steering system deteriorates in the case of emergency collision avoidance. In particular, the wakes of the course resuming after the emergency collision avoidance are caused to be periodic by wrong estimate of the normal pressure and by time delay in the dynamics of the pleasure boat. Therefore, it is found that the electronic control steering system of pleasure boats should have the functions to support estimation of the normal pressure and to compensate the time delay.

Gaze patterns predicting successful collision avoidance in patients with homonymous visual field defects

Aim of the present study was to identify efficient compensatory gaze patterns applied by patients with homonymous visual field defects (HVFDs) under virtual reality (VR) conditions in a dynamic collision avoidance task. Thirty patients with HVFDs due to vascular brain lesions and 30 normal subjects performed a collision avoidance task with moving objects at an intersection under two difficulty levels. Based on their performance (i.e. the number of collisions), patients were assigned to either an “adequate” (HVFDA) or “inadequate” (HVFDI) subgroup by the median split method. Eye and head tracking data were available for 14 patients and 19 normal subjects. Saccades, fixations, mean number of gaze shifts, scanpath length and the mean gaze eccentricity, were compared between HVFDA, HVFDI patients and normal subjects. For both difficulty levels, the gaze patterns of HVFDA patients (N=5) compared to HVFDI patients (N=9) were characterized by longer saccadic amplitudes towards both the affected and the intact side, larger mean gaze eccentricity, more gaze shifts, longer scanpaths and more fixations on vehicles but fewer fixations on the intersection. Both patient groups displayed more fixations in the affected compared to the intact hemifield. Fixation number, fixation duration, scanpath length, and number of gaze shifts were similar between HVFDA patients and normal subjects. Patients with HVFDs who adapt successfully to their visual deficit, display distinct gaze patterns characterized by increased exploratory eye and head movements, particularly towards moving objects of interest on their blind side. In the context of a dynamic environment, efficient compensation in patients with HVFDs is possible by means of gaze scanning. This strategy allows continuous update of the moving objects’ spatial location and selection of the task-relevant ones, which will be represented in visual working memory.

Modeling and Analysis of Human Navigation with Crossing Interferer Using Inverse Optimal Control

AbstractThe walking paths of humans in everyday life exhibit specific characteristics. Our investigation takes the well-established perspective that human locomotion approximately fulfills suitable optimality principles when walking from a starting position to a designated end position. Here, we address the special task of collision avoidance with a crossing interferer. While our model of the dynamics is quite simple, we focus on the task of determining the cost function out of a parametric family, that results in a best fit between the corresponding optimal control-based navigation and given recorded data of human navigation. The resulting bilevel optimization problem combines an optimal control problem on the lower level with a data fitting problem on the upper level. Our solution strategy uses the first-order optimality conditions of the (discretized) optimal control problem to transform the bilevel problem to a standard (one-level) optimization problem.Modeling aspects concerning the walking process and especially the interfering person are discussed. Since human walking motions with a crossing interferer do not seem to be globally optimal, an MPC-like approach distinguishing between obstacle avoidance and free motion is introduced and optimization results using recorded human data are presented.

The neural correlates of impaired collision avoidance in hemianopic patients

The aim of this study was to assess the brain regions associated with impaired performance in a virtual, dynamic collision avoidance task, in a group of patients with homonymous visual field defects (HVFDs) because of unilateral vascular brain lesions. Overall task performance was quantitatively assessed as the number of collisions while crossing an intersection at two levels of traffic density. Twenty-six patients were divided into two subgroups using the median split method: patients with 'performance above average' (HVFD(A), i.e. lower number of collisions) and patients with 'performance below average' (HVFD(B), i.e. higher number of collisions). In order to identify the anatomical structures that might be specifically affected in HVFD(B) patients but spared in HVFD(A) patients, overlap, subtraction and voxel-based lesion-symptom mapping analyses were performed using the MRIcron software. No significant difference in collision avoidance between patients with left- and right-hemispheric lesions was revealed. Separate lesion analysis in 12 patients with right- and 14 patients with left-hemispheric lesions showed that the cortical structures associated with impaired collision avoidance were the parieto-occipital region and posterior cingulate gyrus in the right hemisphere and the inferior occipital cortex and parts of the fusiform (occipito-temporal) gyrus in the left hemisphere. In the present collision avoidance paradigm, impaired performance of patients with right-hemispheric lesions is associated with damage in the dorsal processing stream and potential impact on the visual spatial working memory (WM), while impaired performance of patients with left-hemispheric lesions is associated with damage in the ventral stream and potential impact on the visual object WM.

Age-dependent modulation of sensory reweighting for controlling posture in a dynamic virtual environment

Older adults require more time to reweight sensory information for maintaining balance that could potentially lead to increased incidence of falling in rapidly changing or cognitively demanding environments. In this study, we manipulated the visual surround information during a collision avoidance task in order to investigate how young and elderly adults engage in sensory reweighting under conditions of visual anticipation. Sixteen healthy elderly (age: 71.5 ± 4.9 years; height: 159.3 ± 6.6 cm; mass: 73.3 ± 3.3 kg) and 20 young (age: 22.8 ± 3.3 years; height: 174.4 ± 10.7 cm; mass: 70.1 ± 13.9 kg) participants stood for 240 s on a force platform under two experimental conditions: quiet standing and standing while anticipating randomly approaching virtual objects to be avoided. During both tasks, the visual surround changed every 60 s from a stationary virtual scene (room) to either a moving room or darkness and then back to a stationary scene to evoke sensory reweighting processes. In quiet standing, elderly showed greater sway variability and were more severely affected by the removal or degradation of visual surround information when compared to young participants. During visual anticipation, sway variability was not different between the age groups. In addition, both young and elderly participants were similarly affected by the degradation or removal of the visual surround. These findings suggest that sensory reweighting in a dynamic virtual environment that evokes visual anticipation interacts with postural state anxiety regardless of age. Elderly show less efficient sensory reweighting in quiet standing due to greater visual field dependence possibly associated with fear of falling.

Self-Organized Complementary Coordination: Dynamics of an Interpersonal Collision-Avoidance Task

The current study investigated the movement dynamics of a complementary collision-avoidance task. Participant pairs performed a repetitive targeting task in which they moved computer stimuli back and forth between sets of target locations without colliding into each other. Pairs converged onto a stable relative phase relationship of around 35°, with one participant spontaneously adopting the role of "phase leader" and the other participant adopting the role of "phase follower". In addition, those participants who adopted the role of phase leader tended to exhibit more of a straight-line trajectory between targets, whereas participants who adopted the role of phase follower tended to exhibit a more elliptical trajectory. This role differentiation was essential to task success and reflected the spontaneous relaxation and recruitment of available movement degrees-of-freedom defined across the joint-action system.

Collision avoidance for a mobile robot based on radial basis function hybrid force control technique

Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by hybrid force control algorithm. Since uncertainties from robot dynamics and obstacle degrade the performance of a collision avoidance task, intelligent control is used to compensate for the uncertainties. A radial basis function (RBF) neural network is used to regulate the force field of an accurate distance between a robot and an obstacle in this paper and then simulation studies are conducted to confirm that the proposed algorithm is effective.

Vision-Based Target Tracking and Collision Avoidance for Two Autonomous Robotic Fish

A new type of vision-based autonomous robotic fish capable of 3-D locomotion is developed in this paper. Based on our robotic fish prototype, the forces and moments acting on its fins and body are analyzed, and the governing motion equations are derived. We further investigate a decentralized control method in target-tracking and collision-avoidance task for two autonomous robotic fish. Most of previous work on the task strategies of autonomous robots is focused on terrestrial robots and seldom deals with underwater applications due to the uncertainties and complexity in a hydro environment. To address this challenge in such an underwater task, a situated-behavior-based decentralized control is employed on each robotic fish according to its visual data. On dealing with motion planning of the fish during target tracking and collision avoidance, a control law by a combination of an attractive force toward a target and a repulsive force for collision avoidance is utilized. Experimental results of the task performed by two autonomous robotic fish validate the effectiveness of the proposed method.

Detection of hypofrontality in drivers with Alzheimer's disease by near-infrared spectroscopy

It is important to appropriately evaluate the driving performance of elderly persons. In the present study, near-infrared spectroscopy (NIRS) was employed to investigate differences of brain function between individuals with Alzheimer's disease ( n = 12) and healthy elderly controls ( n = 14) while they were being tested using a driving simulator. Changes of the oxyhemoglobin level in the prefrontal areas of each subject were measured by NIRS during a driving task (collision avoidance). Compared with healthy controls, the Alzheimer's disease group showed a less prominent increase of oxyhemoglobin in the prefrontal cortex during the collision avoidance task. The correlation between delay in braking and changes of oxyhemoglobin was positive in the healthy controls and negative in the Alzheimer's disease group, suggesting that a task-related prefrontal increase of oxyhemoglobin has different implications under normal and pathological conditions. NIRS is a potentially useful tool for real-time monitoring of prefrontal activity during simulated or actual driving.

Transfer effects on communication and collision avoidance behavior from playing a three-dimensional auditory game based on a virtual auditory display

Transfer effects on two everyday auditory skills from playing an auditory game using a virtual auditory display (VAD) were investigated using two groups of 20 normally sighted participants. Representative auditory skills of blindfolded participants were pre-tested using communication and collision avoidance tasks. They performed the tasks two weeks later. Participants in a training group played the VAD-based game on seven days (30 min/day) during the two weeks: control group participants did not. Playing the VAD-based game significantly increased face-contacts in the communication task and significantly improved participants’ collision avoidance. No significant differences were found between the groups’ subjective ratings of the rated tension levels during the communication task or between rated levels for the collision threat. Performance revealed transfer effects of playing the VAD-based game on communication behaviors in social interaction and on avoidance of approaching objects: VAD-based games are effective training tools for auditory skills used in daily life.

Five‐ to twelve‐year‐olds' control of movement velocity in a dynamic collision avoidance task

We investigated age‐related differences in a dynamic collision avoidance task that bears a resemblance to pedestrian road crossing. Five‐ to seven‐year‐old children, ten‐ to twelve‐year‐old children and adults were instructed to push a doll across a small‐scale road between two toy vehicles, which approached one after the other. We analysed the number of attempted crossings, the number of collisions, movement onset times and movement velocity control. The youngest children attempted to cross less often, but collided more frequently than the adults. This age effect could be attributed to differences in the way the children and adults controlled movement velocity. The youngest children attained the velocity that was required for safe travel too late, particularly when the gaps between the toy vehicles were small. The age differences in movement onset strategies were less clear‐cut. The findings are discussed within a framework that proposes distinct roles of vision in action planning and action production.

Travel path conditions dictate the manner in which individuals avoid collisions

The ability to perceive the motion of approaching objects and to make appropriate adjustments to avoid collisions is an essential component of safe locomotion through the environment. No previous study has looked at actual behavioural responses in a realistic collision avoidance task. We investigated individuals’ collision avoidance behaviour with an approaching object in order to understand the visual information used to accomplish the task. We found that when individuals were walking towards a goal without any restrictions, a change in travel path occurred at the same time, independent of the object's approach velocity. However, the lateral rate of change in the travel path was significantly slower for the slower approach velocity. We found that when a restriction was present along the travel path, individuals were exposed to the object's properties for longer and a change in travel path occurred later for slowest approaching velocities than for the fastest approaching velocities. The results suggest that individuals are capable of determining TTC from an approaching object during actual self-motion, but the motor parameter it modulates is different for different circumstances.

A MULTI-LAYER ANALOG/DIGITAL ARCHITECTURE FOR AUTONOMOUS LOCOMOTION IN A HEXAPOD ROBOT WITH SENSORY FEEDBACK

In this paper a new architecture based on a multi-layer analog/digital control system is introduced and applied to an autonomous hexapod robot. The robot structure that consists of 18 degrees of freedom, is controlled by a network of multiple interconnected modules. The system can be tele-operated by a PC through a wireless communication link but it can also operate autonomously by using the information gathered from the sensory system equipped on board. Therefore various methodologies on bio-robot control can be directly implemented and experimentally validated. A set of experimental tests was carried out to characterize the robot performance when employed to accomplish different tasks. The experimental results acquired during a collision avoidance task are also reported and discussed.

Planning and Control in a Manual Collision Avoidance Task by Children with Hemiparesis

We examined whether deficits in planning and control during a manual collision avoidance task in children with hemiparesis are associated with damage to the left or right hemisphere (LHD and RHD). Children pushed a doll across a scale-size road between two approaching toy cars. Movement onset and velocity served as indicators of planning and control. In Experiment 1, children with hemiparesis collided more frequently, and controlled velocity less appropriately compared to typically-developing children. Children with LHD initiated their movement later than children with RHD. Experiment 2 compared the preferred and non-preferred hand of children with LHD and RHD. Children with RHD crossed less with their non-preferred hand, while children with LHD initiated later than children with RHD. Moreover, the groups showed differences in velocity control. It is argued that planning deficits may be related to LHD. The hypothesized association between control deficits and RHD, however, was not confirmed.

Range estimation on a robot using neuromorphic motion sensors

Neuromorphic motion sensors using analog very large scale integrated technology are attractive for use on battery powered robots which require a low payload. Their features include low power consumption, continuous computation, light-weight, and robustness to different light and contrast conditions. Their outputs are not compatible with controllers that require precise measurements from their sensors. We describe a preliminary investigation into neural architectures that can translate information from these type of sensors into an output suitable for controlling the motor outputs of a robot. In this work, we use a neural network to produce an output that is similar to the range measurements of infrared range sensors, and we use this output to guide the behavior of the robot in a collision-avoidance task.

동역학 기반의 지능 힘제어 방식을 이용한 이동 로봇의 장애물 회피에 대한 연구

In this paper, a new collision avoidance algorithm based on the dynamic model of a mobile robot is proposed. In order to avoid obstacles on the path of a mobile robot, intelligent force control is used to regulate accurate distance between a robot and an obstacle. Since uncertainties from robot and environment dynamics degrade the performance of a collision avoidance task, neural network is used to compensate for uncertainties so that the collision avoidance can be performed intelligently. Simulation studies are conducted to confirm the proposed collision avoidance tracking control algorithm.

Fusion of laser and visual data for robot motion planning and collision avoidance

In this paper, a method for inferring scene structure information based on both laser and visual data is proposed. Common laser scanners employed in contemporary robotic systems provide accurate range measurements, but only in 2D slices of the environment. On the other hand, vision is capable of providing dense 3D information of the environment. The proposed fusion scheme combines the accuracy of laser sensors with the broad visual fields of cameras toward extracting accurate scene structure information. Data fusion is achieved by validating 3D structure assumptions formed according to 2D range scans of the environment, through the exploitation of visual information. The proposed methodology is applied to robot motion planning and collision avoidance tasks by using a suitably modified version of the vector field histogram algorithm. Experimental results confirm the effectiveness of the proposed methodology.

Experimental Investigation of Predictive Probabilistic and Temporal Conflict Avoidance Displays

Numerous automated systems are currently in use to assist controllers during air and naval traffic management. However, inferring the future intentions and courses of numerous aircraft or ships at various points in time remains problematic due to a variety of control disturbances. In this paper, a new graphical display concept was evaluated. This display concept provides predictive information about the time, location, and probability of potential traffic conflicts in the form of topological contour displays that were superimposed onto conventional traffic information. Performances on two formats of the new graphical display were compared to a conventional display that does not present predictive traffic information. Participants in the study engaged in a ship control collision avoidance task by performing a series of ship manoeuvres to minimize the danger levels of potential collisions. Although the results of the study are pending, it is hypothesized that the new graphical displays will assist participants in making improved manoeuvring decisions to avoid potential conflicts compared to the conventional display.

高速センサフィードバックに基づく把握行動

In this paper grasping of a dynamically moving object is achieved using high-speed visual and force feedback. First a hierarchical processing model based on high-speed sensory feedback to realize manipulation in a changing environment is proposed. In this model high-speed sensory feedback is used at hierarchical three stages: (1) servo control, (2) motion planning, and (3) switching of motion planners. Because the motion planners are switched according to an external environment at a high rate, responsiveness and flexibility to dynamic changes of the environment is achieved. Next based on the proposed model a manipulation algorithm using high-speed visual and force feedback is proposed, in which a grasping task, an object handling task, and a collision avoidance task are executed. At last experimental results are shown based on a sensory-motor fusion system with a dextrous hand-arm and a high-speed active vision.

The Integrated Design of Fuzzy Collision-Avoidance and H∞-Autopilots on Ships

Collision avoidance remains the most important concern for ships at sea. Despite the electronic equipment now fitted on ships to support the mariner, expert experience is still essential when a ship is in danger of colliding with the others. To include these experts' experiences to resolve the problems of collision, we have designed a fuzzy collision-avoidance expert system that includes a knowledge base to store facts and rules, an inference engine to simulate experts' decisions and a fuzzy interface device. Either a quartermaster or an autopilot system can then implement the avoidance action proposed in the research. To perform the task of collision-avoidance effectively, a robust autopilot system using the state space H∞ control methodology has been designed to steer a ship safely for various conditions at sea in performing course keeping, course-changing and route-tracking more robustly. The integration of fuzzy collision-avoidance and H∞autopilot systems is then proposed in this paper.