A vehicular vision system includes a camera having a lens and a CMOS photosensor array having a plurality of photosensor elements. The camera is disposed at an interior portion of a vehicle equipped with the vehicular vision system. The camera one of (i) views exterior of the equipped vehicle through the windshield of the equipped vehicle and forward of the equipped vehicle and (ii) views from the windshield of the equipped vehicle into the interior cabin of the equipped vehicle. A control includes an image processor that processes image data captured by the photosensor array. The image processor processes captured image data to detect an object viewed by the camera. The photosensor array is operable at a plurality of exposure periods and at least one exposure period of the plurality of exposure periods is dynamically variable.

Vehicular vision system

This paper proposes a feedback control scheme for an omnidirectional holonomic autonomous platform, which is equipped with three lateral orthogonal-wheel assemblies. Firstly, the dynamic properties of the platform are studied, and a dynamic model suitable for the application of control is derived. The control scheme constructed is of the resolved-acceleration type, with PI and PD feedback. The control scheme was experimentally applied to an actual mobile robotic platform. The results obtained show that full omnidirectionality can be achieved with decoupled rotational and translational motions. Omnidirectionality is one of the principal requirements for mobile robots designed for health-care and other general-hospital services.

Feedback Control of an Omnidirectional Autonomous Platform for Mobile Service Robots

A driver assistance system for a vehicle includes an imaging device disposed at an exterior portion of a vehicle. With the imaging device disposed at the exterior portion of the vehicle, the imaging device has a field of view at least one of rearward of the vehicle and sideward of the vehicle. A control utilizes edge detection in processing image data captured by the imaging device. Responsive at least in part to processing of captured image data by the control, the control determines that an object is present in the field of view of the imaging device. The control is operable to determine that the imaging device is misaligned. The control, responsive to a determination of misalignment of the imaging array sensor, is operable to at least partially compensate for the determined misalignment of the imaging device.

Driver assistance system for vehicle

A synthesis of methods from cybernetics an AI yields a concept of intelligence for autonomous mobile systems that integrates closed-loop visual perception and goal-oriented action cycles using spatiotemporal models. In a layered architecture, systems dynamics methods with differential models prevail on the lower, data-intensive levels, but on higher levels, AI-type methods are used. Knowledge about the world is geared to classes of objects and subjects. Subjects are defined as objects with additional capabilities of sensing, data processing, decision making, and control application. Specialist processes for visual detection and efficient tracking of class members have been developed. On the upper levels, individual instantiations of these class members are analyzed jointly in the task context, yielding the situation for decision making. As an application, vertebrate-type vision for tasks in vehicle guidance in naturally perturbed environments was investigated with a distributed PC system. Experimental results with the test vehicle VAMoRs are discussed.

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Dynamic vision-based intelligence

Visual routines for vehicle control

This text presents the proceedings of a conference on intelligent autonomous systems. Papers contribute solutions to the task of designing autonomous systems that are capable of operating independently of a human in partially structured and unstructured environments. For specific application, these systems should also learn from their actions in order to improve and optimize planning and execution of new tasks. There are numerous disciplines that contribute to the design of autonomous systems, including computer sciences, physics, electronics, computer engineering and mechanical engineering. One of the most difficult tasks is system integration, where systems such sensors, vision systems, controllers and machine elements are tied together to a functional entity. The papers bound in these proceedings discuss the results of numerous research endeavours and present the state of the art to obtain autonomy.

L. O. Hertzberger

Papers

Intelligent autonomous systems : IAS-4 : Proceedings of the international Conference Karlsruhe, Germany March 27-30,1995