Direct Collision Course Research Articles

A Robust Visual System for Looming Cue Detection Against Translating Motion.

Collision detection is critical for autonomous vehicles or robots to serve human society safely. Detecting looming objects robustly and timely plays an important role in collision avoidance systems. The locust lobula giant movement detector (LGMD1) is specifically selective to looming objects which are on a direct collision course. However, the existing LGMD1 models cannot distinguish a looming object from a near and fast translatory moving object, because the latter can evoke a large amount of excitation that can lead to false LGMD1 spikes. This article presents a new visual neural system model (LGMD1) that applies a neural competition mechanism within a framework of separated ON and OFF pathways to shut off the translating response. The competition-based approach responds vigorously to monotonous ON/OFF responses resulting from a looming object. However, it does not respond to paired ON-OFF responses that result from a translating object, thereby enhancing collision selectivity. Moreover, a complementary denoising mechanism ensures reliable collision detection. To verify the effectiveness of the model, we have conducted systematic comparative experiments on synthetic and real datasets. The results show that our method exhibits more accurate discrimination between looming and translational events-the looming motion can be correctly detected. It also demonstrates that the proposed model is more robust than comparative models.

China’s BRI developmental agency in its own words: A content analysis of key policy documents

Since its announcement in 2013, the Belt and Road Initiative (BRI) has inspired an ever-growing stream of literature cutting across several disciplines, with highest concentration of studies in the social sciences. Unsurprisingly a great deal of these studies are concerned with the rationale behind this massive undertaking and its potential impact in the current world order. Here a clear rift is apparent between those who think of it as a tool serving China’s geopolitical interests and rise at the world stage, and those who see it as a more nebulous and fragmented undertaking driven by domestic economic and political pressures. A similar concern is reflected in a smaller body of literature that looks at the BRI from a development angle, the dominant inquiry line revolving around its likely impact in global development governance and the underlying neoliberal cooperation norms and practices. Here too there is a clear divide between those who see China’s increasing development agency as a positive complement and those who perceive it in a direct collision course with the neoliberal aid paradigm. This dichotomy of interpretations project two contrasting images of China’s development agency that are often difficult to reconcile. This study contributes to this body of literature by providing a profile of China’s development agency according to its own words. Since 2015 a raft of BRI policy documents have been published by Beijing to fill the initial void and regain control over the narrative. Through a content analysis of key policy papers and speeches, we attempt to uncover what are the initiative’s aims, governance mechanisms, normative under pinnings, and targeted areas as per the official discourse. In doing so we hope to bring more clarity as to the nature of China developmental agency. Based on our findings we argue that much like its domestic development model, China’s development cooperation approach is pragmatically hybrid with the rhetoric showing clear signs of convergence but also divergence with the dominant paradigm. The evolving discourse suggests a highly fluid approach and thus a work in constant progress, which progression hinges upon reactive and cumulative adjustments to feedback as the initiative is rolled out.

Fiddler crabs ignore near misses when threatened from all sides

Everyone suffers with attention overload from time to time. Sometimes there are simply too many meetings and deadlines for one brain to keep track of, so you have to prioritise. Yet, compared with the life and death attention grabbers that stalk many creatures’ lives, we've got it easy. ‘Prey animals are often exposed to multiple simultaneous threats, which significantly complicates the decision-making process’, says Zahra Bagheri from the University of Western Australia. So how do animals that are facing several threats simultaneously prioritise which one, or ones, to take seriously?To find out how fiddler crabs respond when confronted with two looming threats, Bagheri, Callum Donohue and Jan Hemmi, also from the University of Western Australia, rigged up a pair of black spheres suspended on fishing line travelling threateningly toward the crustaceans: one on a direct collision course and the second coming in at an angle to produce an alarming near miss. Intriguingly, the crabs that were on a near-miss collision course began scuttling for safety when the alarming ball was as much as 300 cm away. However, the crabs that were in direct line with the incoming sphere stood their ground until it was within 100 cm; only then did they beat a retreat. In contrast, when confronted with both inbound balls simultaneously, instead of turning tail when the near-miss ball was within 300 cm, the crabs held on until the ball heading straight for them came within a threatening 100 cm. The crabs appeared to be completely disregarding the less dangerous threat, focusing exclusively on the inbound ball that could genuinely bowl them over.‘Crabs that face multiple predators simultaneously behave as if they only face the single, directly approaching predator’, says Bagheri, adding, ‘this suggests that the crabs do not perceive, or do not respond to, the increased risk of predation posed by two simultaneous predators’. The team suspects that the crabs weigh up the relative dangers of each impending threat and focus on the one that poses the greatest risk, ignoring others that would simply result in a narrow escape. After all, there's only so much attention to go around, so the key to survival is to use it wisely.

Infants’ Brain Responses to Looming Danger: Degeneracy of Neural Connectivity Patterns

A fundamental property of most animals is the ability to see whether an object is approaching on a direct collision course and, if so, when it will collide. Using high-density electroencephalography in infants and a looming stimulus approaching under three different accelerations, we previously found how visual information for impending collision is sustained in the young human nervous system. In the present study, using longitudinal data on 25 infants at 4–5 months and 12–13 months, we show that infants’ looming-related brain activity is clearly localized in the visual cortex (V1) following retinotopic mapping, but is highly adaptive in its organization otherwise. Analyzing the orientation of electrical source flow, we provide evidence for a high degree of variability, spread across a relatively large area of the visual cortex. The findings reveal a highly dynamic functional organization, with connectivity patterns constantly emerging and changing in many different directions between trials. This suggests degeneracy of neural connectivity patterns through reentry principles, where neurons temporarily assemble to enable an appropriate looming response with the necessary precision.

Complex object motion represented by context-dependent correlated activity of visual interneurones.

Accurate and adaptive encoding of complex, dynamic visual information is critical for the survival of many animals. Studies across a range of taxa have investigated behavioral and neuronal responses to objects that represent a threat, such as a looming object approaching along a direct collision course. By investigating neural mechanisms of avoidance behaviors through recording multineuronal activity, it is possible to better understand how complex visual information is represented in circuits that ultimately drive behaviors. We used multichannel electrodes to record from the well‐studied locust nervous system to explore how object motion is reflected in activity of correlated neural activity. We presented locusts (Locusta migratoria) with objects that moved along one of 11 unique trajectories and recorded from descending interneurons within the ventral nerve cord. Spike sorting resulted in 405 discriminated units across 20 locusts and we found that 75% of the units responded to some form of object motion. Dimensionality reduction through principal component (PCA) and dynamic factor (DFA) analyses revealed population vector responses within individuals and common firing trends across the pool of discriminated units, respectively. Population vector composition (PCA) varied with the stimulus and common trends (DFA) showed unique tuning related to changes in the visual size and trajectory of the object through time. These findings demonstrate that this well‐described collision detection system is more complex than previously envisioned and will drive future experiments to explore fundamental principles of how visual information is processed through context‐dependent dynamic ensembles of neurons to initiate and control complex behavior.

Background visual motion affects responses of an insect motion-sensitive neuron to objects deviating from a collision course.

Stimulus complexity affects the response of looming sensitive neurons in a variety of animal taxa. The Lobula Giant Movement Detector/Descending Contralateral Movement Detector (LGMD/DCMD) pathway is well‐characterized in the locust visual system. It responds to simple objects approaching on a direct collision course (i.e., looming) as well as complex motion defined by changes in stimulus velocity, trajectory, and transitions, all of which are affected by the presence or absence of background visual motion. In this study, we focused on DCMD responses to objects transitioning away from a collision course, which emulates a successful locust avoidance behavior. We presented each of 20 locusts with a sequence of complex three‐dimensional visual stimuli in simple, scattered, and progressive flow field backgrounds while simultaneously recording DCMD activity extracellularly. DCMD responses to looming stimuli were generally characteristic irrespective of stimulus background. However, changing background complexity affected, peak firing rates, peak time, and caused changes in peak rise and fall phases. The DCMD response to complex object motion also varied with the azimuthal approach angle and the dynamics of object edge expansion. These data fit with an existing correlational model that relates expansion properties to firing rate modulation during trajectory changes.

Fly visual system inspired artificial neural network for collision detection

This work investigates one bio-inspired collision detection system based on fly visual neural structures, in which collision alarm is triggered if an approaching object in a direct collision course appears in the field of view of a camera or a robot, together with the relevant time region of collision. One such artificial system consists of one artificial fly visual neural network model and one collision detection mechanism. The former one is a computational model to capture membrane potentials produced by neurons. The latter one takes the outputs of the former one as its inputs, and executes three detection schemes: (i) identifying when a spike takes place through the membrane potentials and one threshold scheme; (ii) deciding the motion direction of a moving object by the Reichardt detector model; and (iii) sending collision alarms and collision regions. Experimentally, relying upon a series of video image sequences with different scenes, numerical results illustrated that the artificial system with some striking characteristics is a potentially alternative tool for collision detection.

Spatiotemporal stimulus properties modulate responses to trajectory changes in a locust looming-sensitive pathway

The lobula giant movement detector (LGMD) and descending contralateral movement detector (DCMD) constitute one motion-sensitive pathway in the locust visual system that is implicated in collision-avoidance behaviors. While this pathway is thought to respond preferentially to objects approaching on a direct collision course, emerging studies suggest the firing rate is able to monitor more complicated movements that would occur under natural conditions. While previous studies have compared the response of the DCMD to objects on collision courses that travel at different speeds, velocity has not been manipulated for other simple or compound trajectories. Here we test the possibility that the LGMD/DCMD pathway is capable of responding uniquely to complex aspects of object motion, including translation and trajectory changes at different velocities. We found that the response of the DCMD to translational motion initiated in the caudal visual field was a low-amplitude peak in firing rate that occurred before the object crossed 90° azimuth that was invariant to different object velocities. Direct looms at different velocities resulted in peak firing rates that occurred later in time and with greater amplitude for higher velocities. In response to transitions from translational motion to a collision course, the firing rate change depended on both the location within the visual field and the velocity. These results suggest that this pathway is capable of conveying information about multiple properties of a moving object's trajectory.

Longitudinal Study of Looming in Infants with High-Density EEG

A rapidly approaching object provides information about the object's approach and how imminent a collision is. Prospective control when responding to a looming virtual object approaching on a direct collision course was studied longitudinally in 10 infants aged 5/6 and 12/13 months. Different characteristics of the looming-related visual evoked potential (VEP) responses from infants' brain electrical recordings (EEG) were explored and compared between the infants at these different ages. The aim of this study was to find evidence for infant brain electrical responses coherent with a looming stimulus approaching the infant under three different accelerations. It was also investigated whether the use of different timing strategies to estimate the loom's time-to-collision would produce differences in the EEG recordings. The results showed that the timing and the duration of the VEP responses differed with age. At the age of 5/6 months, infants showed VEP peaks earlier in the looming sequence and VEP responses with longer duration than when they were 12/13 months old. Results from the timing-strategy analysis showed that with age, 4 infants shifted from a less efficient timing strategy involving the loom's velocity to the more efficient strategy involving the loom's time-to-collision. Further, it was found that peak VEP activation in the investigated areas propagated across the cortex, showing the highest observed activation in the occipital area at the age of 5/6 months, whereas the parietal area showed the highest activation when the infants were 12/13 months. The decrease in processing time together with a peak VEP response closer to the loom's time-to-collision indicate a developmental trend in infants' prediction of an object's time-to-collision. This developmental trend is further substantiated by the shift from a less efficient to a more efficient timing strategy and by evidence of propagated peak VEP activation towards higher information processing areas in the visual pathway with age. As infants grow older and become more mobile, one of the underlying causes of the developmental trend found in our study could be due to an increase in locomotor experience. More follow-up research is needed to investigate the relation between behavioural development and changes in brain activity associated with infants' perception of looming motion.

A looming-sensitive pathway responds to changes in the trajectory of object motion

Two identified locust neurons, the lobula giant movement detector (LGMD) and its postsynaptic partner, the descending contralateral movement detector (DCMD), constitute one motion-sensitive pathway in the visual system that responds preferentially to objects that approach on a direct collision course and are implicated in collision-avoidance behavior. Previously described responses to the approach of paired objects and approaches at different time intervals (Guest BB, Gray JR. J Neurophysiol 95: 1428-1441, 2006) suggest that this pathway may also be affected by more complicated movements in the locust's visual environment. To test this possibility we presented stationary locusts with disks traveling along combinations of colliding (looming), noncolliding (translatory), and near-miss trajectories. Distinctly different responses to different trajectories and trajectory changes demonstrate that DCMD responds to complex aspects of local visual motion. DCMD peak firing rates associated with the time of collision remained relatively invariant after a trajectory change from translation to looming. Translatory motion initiated in the frontal visual field generated a larger peak firing rate relative to object motion initiated in the posterior visual field, and the peak varied with simulated distance from the eye. Transition from translation to looming produced a transient decrease in the firing rate, whereas transition away from looming produced a transient increase. The change in firing rate at the time of transition was strongly correlated with unique expansion parameters described by the instantaneous angular acceleration of the leading edge and subtense angle of the disk. However, response time remained invariant. While these results may reflect low spatial resolution of the compound eye, they also suggest that this motion-sensitive pathway may be capable of monitoring dynamic expansion properties of objects that change the trajectory of motion.

Defence behaviours of the praying mantis Tenodera aridifolia in response to looming objects

Defence responses to approaching objects were observed in the mantis Tenodera aridifolia. The mantis showed three kinds of behaviour, fixation, evasion and cryptic reaction. The cryptic reaction consisted of rapid retraction of the forelegs under the prothorax or rapid extending of the forelegs in the forward direction. Obstructing the mantis’ sight decreased its response rates, suggesting that the visual stimuli generated by an approaching object elicited the cryptic reaction. The response rate of the cryptic reactions was highest for objects that approached on a direct collision course. Deviation in a horizontal direction from the direct collision course resulted in a reduced response. The response rate of the cryptic reaction increased as the approaching velocity of the object increased, and the rate decreased as the object ceased its approach at a greater distance from the mantis. These results suggest that the function of the observed cryptic reactions is defence against impending collisions. The possible role of the looming-sensitive neuron in the cryptic reaction is also discussed.

Collision-Sensitive Neurons in the Optic Tectum of the Bullfrog,Rana catesbeiana

In this study, we examined the neuronal correlates of frog collision avoidance behavior. Single unit recordings in the optic tectum showed that 11 neurons gave selective responses to objects approaching on a direct collision course. The collision-sensitive neurons exhibited extremely tight tuning for collision bound trajectories with mean half-width at half height values of 0.8 and 0.9° (n = 4) for horizontal and vertical deviations, respectively. The response of frog collision-sensitive neurons can be fitted by a function that simply multiplies the size dependence of its response, e(-αθ(t)), by the image's instantaneous angular velocity θ'(t). Using fitting analysis, we showed that the peak firing rate always occurred after the approaching object had reached a constant visual angle of 24.2 ± 2.6° (mean ± SD; n = 8), regardless of the approaching velocity. Moreover, a linear relationship was demonstrated between parameters l/v (l: object's half-size, v: approach velocity) and time-to-collision (time difference between peak neuronal activity and the predicted collision) in the 11 collision-sensitive neurons. In addition, linear regression analysis was used to show that peak firing rate always occurred after the object had reached a constant angular size of 21.1° on the retina. The angular thresholds revealed by both theoretical analyses were comparable and showed a good agreement with that revealed by our previous behavioral experiments. This strongly suggests that the collision-sensitive neurons of the frog comprise a threshold detector, which triggers collision avoidance behavior.

Response properties and receptive field organization of collision-sensitive neurons in the optic tectum of bullfrog, Rana catesbeiana

Many studies have reported that animals will display collision avoidance behavior when the size of retinal image of an object reaches a threshold. The present study aimed to investigate the neural correlates underlying the frog collision avoidance behavior. Different types of visual stimuli simulating the retinal image of an approaching or a recessing object were generated by a computer and presented to the right eye of frog. A multielectrode array was used to examine the activity of collision-sensitive neurons, and single electrode recordings were employed to quantify visual parameter(s) of the frog collision-sensitive neurons. The multielectrode array revealed that 40 neurons in the optic tectum showed selective responsiveness to objects approaching on a direct collision course. The response profiles of these collision-sensitive neurons were similar to those of lobula giant movement detector (LGMD) in the locust or to those of neurons in the pigeon. However, the receptive field (RF) size of the frog neurons [(18.5+/-3.8) degrees, n=33)] was smaller than those of collision-sensitive neurons of the locust and the pigeon. Multielectrode recordings also showed that the collision-sensitive neurons were activated only when the focus of expansion of a looming retinal image was located within the center of its RF. There was a linear relationship between the parameter l/v (l denotes half-size of the object, v denotes approaching velocity) and time-to-collision (time difference between the peak of the neuronal activity and the predictive collision) in 16 collision-sensitive neurons. Theoretical consideration showed that the peak firing rate always occurred at a fixed delay of (60.1 +/- 39.5) ms (n=16) after the object had reached a constant angular size of (14.8 +/- 3.4) degrees (n=16) on the retina. The results may help clarify the mechanisms underlying the collision avoidance behavior in bullfrog.

Seeing it coming: infants’ brain responses to looming danger

A fundamental property of most animals is the ability to see whether an object is approaching on a direct collision course and, if so, when it will collide. Using high-density electroencephalography in 5- to 11-month-old infants and a looming stimulus approaching under three different accelerations, we investigated how the young human nervous system extracts and processes information for impending collision. Here, we show that infants' looming related brain activity is characterised by theta oscillations. Source analyses reveal clear localised activity in the visual cortex. Analysing the temporal dynamics of the source waveform, we provide evidence that the temporal structure of different looming stimuli is sustained during processing in the more mature infant brain, providing infants with increasingly veridical time-to-collision information about looming danger as they grow older and become more mobile.

Collision course by transformation of coordinates and plane decomposition

SUMMARYThis paper deals with the problem of collision course checking in a dynamic environment for mobile robotics applications. Our method is based on the relative kinematic equations between moving objects. These kinematic equations are written under polar form. A transformation of coordinates is derived. Under this transformation, collision between two moving objects is reduced to collision between a stationary object and a virtual moving object. In addition to the direct collision course, we define the indirect collision course, which is more critical and difficult to detect. Under this formulation, the collision course problem is simplified, and complex scenarios are reduced to simple scenarios. In three-dimensional (3D) settings, the working space is decomposed into two planes: the horizontal plane and the vertical plane. The collision course detection in 3D is studied in the vertical and horizontal planes using 2D techniques. This formulation brings important simplifications to the collision course detection problem even in the most critical and difficult scenarios. An extensive simulation is used to illustrate the method in 2D and 3D working spaces.

Temporal dynamics of travelling theta wave activity in infants responding to visual looming

AbstractA fundamental property of most animals is the ability to see whether an object is approaching on a direct collision course and, if so, when it will collide. Using high-density electroencephalography in 5- to 11-month-old infants and a looming stimulus approaching under three different accelerations, we investigated how the young human nervous system extracts and processes information for impending collision. Here we show that infants' looming related brain activity is characterized by theta oscillations. Source analyses reveal clear localised activity in the visual cortex. Analysing the temporal dynamics of the source waveform, we provide evidence that the temporal structure of different looming stimuli is sustained during processing in the more mature infant brain, providing infants with increasingly veridical time-to-collision information about looming danger as they grow older and become mobile.

The Forgotten History of the Protestant Crusade: Religious Liberalism in Ireland1

Irish historians do not generally identify religious liberalism as a feature of the 1820s. Instead, they have mapped religious conflict onto increasingly binary conflicts in the socio‐economic, cultural, and political spheres. The “Second Reformation” missionary movement put evangelicals and Catholics on a direct collision course and, consequently, historians have argued that it was a key factor in the emergence both of Irish Catholic nationalism and Protestant defensive co‐operation. However, the Crusade also produced a strong Protestant backlash alongside the growing sectarian conflict. In County Limerick, for example, two versions of Church of Ireland opposition emerged during 1820, among high church clergy including Bishop Jebb and among liberal Protestant gentlemen. Instead of closing down debate into rigid binary opposition along sectarian lines, the Limerick evidence shows that the Crusade produced a much more complex religious, social, and political debate than historians have recognised which, in turn, made possible a wider range of responses to key Irish problems.

A bio-inspired visual collision detection mechanism for cars: Combining insect inspired neurons to create a robust system

The lobula giant movement detector (LGMD) of locusts is a visual interneuron that responds with an increasing spike frequency to an object approaching on a direct collision course. Recent studies involving the use of LGMD models to detect car collisions showed that it could detect collisions, but the neuron produced collision alerts to non-colliding, translating, stimuli in many cases. This study presents a modified model to address these problems. It shows how the neurons pre-synaptic to the LGMD show a remarkable ability to filter images, and only colliding and translating stimuli produce excitation in the neuron. It then integrates the LGMD network with models based on the elementary movement detector (EMD) neurons from the fly visual system, which are used to analyse directional excitation patterns in the biologically filtered images. Combining the information from the LGMD neuron and four directionally sensitive neurons produces a robust collision detection system for a wide range of automotive test situations.

Visual motion pattern extraction and fusion for collision detection in complex dynamic scenes

Detecting colliding objects in complex dynamic scenes is a difficult task for conventional computer vision techniques. However, visual processing mechanisms in animals such as insects may provide very simple and effective solutions for detecting colliding objects in complex dynamic scenes. In this paper, we propose a robust collision detecting system, which consists of a lobula giant movement detector (LGMD) based neural network and a translating sensitive neural network (TSNN), to recognise objects on a direct collision course in complex dynamic scenes. The LGMD based neural network is specialized for recognizing looming objects that are on a direct collision course. The TSNN, which fuses the extracted visual motion cues from several whole field direction selective neural networks, is only sensitive to translating movements in the dynamic scenes. The looming cue and translating cue revealed by the two specialized visual motion detectors are fused in the present system via a decision making mechanism. In the system, the LGMD plays a key role in detecting imminent collision; the decision from TSNN becomes useful only when a collision alarm has been issued by the LGMD network. Using driving scenarios as an example, we showed that the bio-inspired system can reliably detect imminent colliding objects in complex driving scenes.

A bio-inspired visual collision detection mechanism for cars: Optimisation of a model of a locust neuron to a novel environment

The lobula giant movement detector (LGMD) neuron of locusts has been shown to preferentially respond to objects approaching the eye of a locust on a direct collision course. Computer simulations of the neuron have been developed and have demonstrated the ability of mobile robots, interfaced with a simulated LGMD model, to avoid collisions. In this study, a model of the LGMD neuron is presented and the functional parameters of the model identified. Models with different parameters were presented with a range of automotive video sequences, including collisions with cars. The parameters were optimised to respond correctly to the video sequences using a range of genetic algorithms (GAs). The model evolved most rapidly using GAs with high clone rates into a form suitable for detecting collisions with cars and not producing false collision alerts to most non-collision scenes.