Motion Templates Research Articles

The mechanism of interaction between visual flow and eye velocity signals for heading perception.

A translating eye receives a radial pattern of motion that is centered on the direction of heading. If the eye is rotating and translating, visual and extraretinal signals help to cancel the rotation and to perceive heading correctly. This involves (1) an interaction between visual and eye movement signals and (2) a motion template stage that analyzes the pattern of visual motion. Early interaction leads to motion templates that integrate head-centered motion signals in the visual field. Integration of retinal motion signals leads to late interaction. Here, we show that retinal flow limits precision of heading. This result argues against an early, vector subtraction type of interaction, but is consistent with a late, gain field type of interaction with eye velocity signals and neurophysiological findings in area MST of the monkey.

Adapting to Hostile Architectural Environments

Adapting to Hostile Architectural Environments

Heading detection using motion templates and eye velocity gain fields.

Eye or head rotation would influence perceived heading direction if it were coded by cells tuned only to retinal flow patterns that correspond to linear self-movement. We propose a model for heading detection based on motion templates that are also Gaussian-tuned to the amount of rotational flow. Such retinal flow templates allow explicit use of extra-retinal signals to create templates tuned to head-centric flow as seen by the stationary eye. Our model predicts an intermediate layer of 'eye velocity gain fields' in which 'rate-coded' eye velocity is multiplied with responses of templates sensitive to specific retinal flow patterns. By combination of the activities of one retinal flow template and many units with an eye velocity gain field, a new type of unit appears: its preferred retinal flow changes dynamically in accordance with the eye rotation velocity. This unit's activity becomes thereby approximately invariant to the amount of eye rotation. The units with eye velocity gain fields from the motion-analogue of the units with eye position gain fields found in area 7a, which according to our general approach, are needed to transform position from retino-centric to head-centric coordinates. The rotation-tuned templates can also provide rate-coded visual estimates of eye rotation to allow a pure visual compensation for rotational flow. Our model is consistent with psychophysical data that indicate a role for extra-retinal as well as visual rotation signals in the correct perception of heading.

Motion templates with eye velocity gain fields for transformation of retinal to head centric flow.

Heading perception from the optic flow is more difficult during eye rotations than when the eye is stationary, because the centre of the retinal motion identifies the fixation direction rather than the direction of heading. Eye movement signals helps when motion parallax is absent. This paper distinguishes two different possibilities for interactions between eye movement and visual motion signals to perceive heading with a rotating eye. A pre-motion template transformation changes local retinal velocity into head centric velocity. These velocities then feed head centric motion templates. A post-motion template model combines oculomotor signals with retinal motion templates to arrive at head centric flow templates. The latter scheme involves eye velocity gain fields similar to the eye position gain fields as found in area 7a. We propose that the parietal cortex transforms retinal to head centric direction and retinal to head centric flow on the same principle.

Gait and foot trajectory planning for versatile motions of a six-legged robot

This article deals with the problem of planning and controlling a radially symmetric six-legged walker on an uneven terrain when a smooth time-varying body motion is required. The main difficulties lie on the planning of gaits and foot trajectories. As for the gaits, this article discusses the forward wave gait of a variable duty factor and a variable wave direction. With the commanded body motion, the maximum possible duty factor is computed using the speed limit of the leg swing motion. Guaranteeing this maximum duty factor contributes to obtain higher stability. We prove the “continuity” of this forward wave gait planning algorithm adds the versatility to gaits planned. The foot trajectory planning algorithm dynamically generates a smooth foot trajectory as a function of the instantaneous body motions by modifying standard leg motion templates. The robot can negotiate an uneven terrain by modifying a vertical leg motion by a signal of tactile sensors on the foot. The experiments prove that the robot can successfully track smooth curves with body rotations on an uneven terrain, and thus prove the robustness of the algorithms. © 1997 John Wiley & Sons, Inc.