Dynamic Image-based visual servo control using centroid and optic flow features

This paper considers the question of designing a fully image-based visual servo control for a class of dynamic systems. The work is motivated by the ongoing development of image-based visual servo control of small aerial robotic vehicles. The kinematics and dynamics of a rigid-body dynamical system (such as a vehicle airframe) maneuvering over a flat target plane with observable features are expressed in terms of an unnormalized spherical centroid and an optic flow measurement. The image-plane dynamics with respect to force input are dependent on the height of the camera above the target plane. This dependence is compensated by introducing virtual height dynamics and adaptive estimation in the proposed control. A fully nonlinear adaptive control design is provided that ensures asymptotic stability of the closed-loop system for all feasible initial conditions. The choice of control gains is based on an analysis of the asymptotic dynamics of the system. Results from a realistic simulation are presented that demonstrate the performance of the closed-loop system. To the author's knowledge, this paper documents the first time that an image-based visual servo control has been proposed for a dynamic system using vision measurement for both position and velocity.

Combined optic-flow and stereo-based navigation of urban canyons for a UAV

We present a novel vision-based technique for navigating an Unmanned Aerial Vehicle (UAV) through urban canyons. Our technique relies on both optic flow and stereo vision information. We show that the combination of stereo and optic-flow (stereo-flow) is more effective at navigating urban canyons than either technique alone. Optic flow from a pair of sideways-looking cameras is used to stay centered in a canyon and initiate turns at junctions, while stereo vision from a forward-facing stereo head is used to avoid obstacles to the front. The technique was tested in full on an autonomous tractor at CSIRO and in part on the USC autonomous helicopter. Experimental results are presented from these two robotic platforms operating in outdoor environments. We show that the autonomous tractor can navigate urban canyons using stereoflow, and that the autonomous helicopter can turn away from obstacles to the side using optic flow. In addition, preliminary results show that a single pair of forward-facing fisheye cameras can be used for both stereo and optic flow. The center portions of the fisheye images are used for stereo, while flow is measured in the periphery of the images.

Terrain following using wide field optic flow

Wall and terrain following is a challenging problem for small, fast, and fragile robot vehicles. This paper presents a robust algorithm based on wide field integration of optic flow. Solutions for two dimensional and three dimensional wall following is provided for vehicles with non-holonomic velocity constraints that ensure that the focus of expansion of the flow field is known. The potential of the proposed algorithm is demonstrated in a simulation environment.

Results of applying sensor fusion to a control system using optic flow

The results from applying a sensor fusion process to an adaptive controller used to balance all inverted pendulum axe presented. The goal of the sensor fusion process was to replace some of the four mechanical measurements, which are known to be sufficient inputs for a linear state feedback controller to balance the system, with optic flow variables. Results from research into the psychology of the sense of balance in humans were the motivation for the investigation of this new type of controller input. The simulated model of the inverted pendulum and the virtual reality environments used to provide the optical input are described. The successful introduction of optical information is found to require the preservation of at least two of the traditional input types and entail increased training till-le for the adaptive controller and reduced performance (measured as the time the pendulum remains upright)

Investigation into the performance of an algorithm for deriving concise descriptions of optic flow fields for real-time control

This paper describes a region-based algorithm for deriving a concise description of a first order optical flow field. The algorithm described achieves performance improvements over existing algorithms without compromising the accuracy of the flow field values calculated. These improvements are brought about by not computing the entire flow field between two consecutive images, but by considering only the flow vectors of a selected subset of the images. The algorithm is presented in the context of a project to balance a bipedal robot using visual information.

Visual processing of optic flow and motor control in the human posterior cingulate sulcus

Previous studies have shown that the human posterior cingulate contains a visual processing area selective for optic flow (CSv). However, other studies performed in both humans and monkeys have identified a somatotopic motor region at the same location (CMA). Taken together, these findings suggested the possibility that the posterior cingulate contains a single visuomotor integration region. To test this idea we used fMRI to identify both visual and motor areas of the posterior cingulate in the same brains and to test the activity of those regions during a visuomotor task. Results indicated that rather than a single visuomotor region the posterior cingulate contains adjacent but separate motor and visual regions. CSv lies in the fundus of the cingulate sulcus, while CMA lies in the dorsal bank of the sulcus, slightly superior in terms of stereotaxic coordinates. A surprising and novel finding was that activity in CSv was suppressed during the visuomotor task, despite the visual stimulus being identical to that used to localize the region. This may provide an important clue to the specific role played by this region in the utilization of optic flow to control self-motion.

Influence of Imposed Optic Flow Characteristics and Intention on Postural Responses

This study examined the influence of both optic flow characteristics and intention on postural control responses. Two groups of 10 adults each were exposed to the room's movement either at 0.6 cm/s (low velocity group) or 1.0 cm/s (high velocity group). All the participants stood in the upright stance inside of a moving room and were informed about the room movement only after the fourth trial as they were asked to resist to its influence. Results revealed that participants from both groups were influenced by the imposed visual stimulus in the first trials, but the coupling strength was weaker for the high velocity group. The request to resist the visual influences decreased visual influences oil body sway, but only for the low velocity group. These results indicate that intention might play a role in stimulus influences on body sway but it is stimulus dependent.

Optic Flow Contribution to Locomotion Adjustments in Obstacle Avoidance

Locomotion generates a visual movement pattern characterized as optic flow. To explore how the locomotor adjustments are affected by this pattern, an experimental paradigm was developed to eliminate optic flow during obstacle avoidance. The aim was to investigate the contribution of optic flow in obstacle avoidance by using a stroboscopic lamp. Ten young adults walked on an 8m pathway and stepped over obstacles at two heights. Visual sampling was determined by a stroboscopic lamp (static and dynamic visual sampling). Three-dimensional kinematics data showed that the visual information about self-motion provided by the optic flow was crucial for estimating the distance from and the height of the obstacle. Participants presented conservative behavior for obstacle avoidance under experimental visual sampling conditions, which suggests that optic flow favors the coupling of vision to adaptive behavior for obstacle avoidance.

Optic flow estimation in fluid images II

[EN] In this report we study a number of fluid optic flow sequences in the context of the FLUID Specific Targeted Research Project - Contract No 513633 founded by the EEC. The main goal of this report is to analyse the behaviour of classical computer vision optic flow techniques when we deal with fluid sequences. We use the optic flow sequences provided by other partners of the FLUID project.

Influence of optic flow on postural control

The study of optic flow on postural control may explain how self-motion perception contributes to postural stability in young males and females and how such function changes in the old falls risk population. Study I: The aim was to examine the optic flow effect on postural control in young people (n=24), using stabilometry and surface-electromyography. Subjects viewed expansion and contraction optic flow stimuli which were presented full field, in the foveral or in the peripheral visual field. Results showed that optic flow stimulation causes an asymmetry in postural balance and a different lateralization of postural control in men and women. Gender differences evoked by optic flow were found both in the muscle activity and in the prevalent direction of oscillation. The COP spatial variability was reduced during the view of peripheral stimuli which evoked a clustered prevalent direction of oscillation, while foveal and random stimuli induced non-distributed directions. Study II was aimed at investigating the age-related mechanisms of postural stability during the view of optic flow stimuli in young (n=17) and old (n=19) people, using stabilometry and kinematic. Results showed that old people showed a greater effort to maintain posture during the view of optic flow stimuli than the young. Elderly seems to use the head stabilization on trunk strategy. Visual stimuli evoke an excitatory input on postural muscles, but the stimulus structure produces different postural effects. Peripheral optic flow stabilizes postural sway, while random and foveal stimuli provoke larger sway variability similar to those evoked in baseline. Postural control uses different mechanisms within each leg to produce the appropriate postural response to interact with extrapersonal environment. Ageing reduce the effortlessness to stabilize posture during optic flow, suggesting a neuronal processing decline associated with difficulty integrating multi-sensory information of self-motion perception and increasing risk of falls.

Optic flow in human vision: MEG reveals a foveo-fugal bias in V1, specialization for spiral space in hMSTs, and global motion sensitivity in the IPS

Abstract We recorded MEG responses from 17 participants viewing random-dot patterns simulating global optic flow components (expansion, contraction, rotation, deformation, and translation) and a random motion control condition. Theta-band (3–7 Hz), MEG signal power was greater for expansion than the other optic flow components in a region concentrated along the calcarine sulcus, indicating an ecologically valid, foveo-fugal bias for unidirectional motion sensors in V1. When the responses to the optic flow components were combined, a decrease in MEG beta-band (17–23 Hz) power was found in regions extending beyond the calcarine sulcus to the posterior parietal lobe (inferior to IPS), indicating the importance of structured motion in this region. However, only one cortical area, within or near the V5/hMT+ complex, responded to all three spiral-space components (expansion, contraction, and rotation) and showed no selectivity for global translation or deformation: we term this area hMSTs. This is the first demonstration of an exclusive region for spiral space in the human brain and suggests a functional role better suited to preliminary analysis of ego-motion than surface pose, which would involve deformation. We also observed that the rotation condition activated the cerebellum, suggesting its involvement in visually mediated control of postural adjustment.

Drosophila Flight Stabilization Depends on Apparent Distances in Optic Flow Field

To perform daily flight tasks, insects rely heavily on their visual perception of a dynamic environment. They must process visual signals quickly and accurately and update their behavior. Flies are vulnerable to environmental disturbances, such as gusts of wind blowing them off course, but they may use the altered visual field to compensate and regain their original course. In studies using Drosophila melanogaster, it has been shown that their corrective responses can be analyzed by measuring changes in their wing beats. By enclosing a tethered fly in a cuboidal visual arena displaying a computerized optic flow field, it is possible to calculate the change in wing beat amplitudes from an infrared shadow of its wings using photodiodes and a custom wing beat analyzer. In this experiment, manipulations ofthe optic flow field are used to create a field where points have varying relative forward speed, to study how the insect performs corrective maneuvers. The results show that Drosophila have a stronger corrective response to the quickly moving, apparently near points compared to the slower moving, apparently distant points. This implies the flies are distinguishing points based on their relative speeds, inferring distance, and adjusting their corrective actions with this information.