Titlebook: Reasoning with Uncertainty in Robotics; International Worksh Leo Dorst,Michiel Lambalgen,Frans Voorbraak Conference proceedings 1996 Spring

共同確定為確

Probabilistic map learning: Necessity and difficulties,rtant aspect of the analysis is concerned with the necessity and the difficulties to maintain correlation between the state variables (the geometric features, the robot). The effects of nonlinearities on uncertainty propagation and the degradation of the sensors‘ uncertainty models are analysed and illustrated through simulation examples.

生存環(huán)境

0302-9743 am, The Netherlands, in December 1995..The book contains 13 revised full papers carefully selected for presentation during the workshop together with six invited papers. Also included are two comprehensive tutorial texts and an introduction by the volume editors. Thus the book is both a competent st

recession

Partially observable markov decision processes for artificial intelligence,ing the theory of Markov decision processes (MDPs) and partially observable Markov decision processes POMDPs. We then outline a novel algorithm for solving POMDPs off line and show how, in many cases, a finite-memory controller can be extracted from the solution to a POMDP. We conclude with a simple example.

Engaging

洞穴

The robot control strategy in a domain with dynamical obstacles,ry planning is fulfilled for providing the robot movement time close to the minimal..The problem of a robot reaching a moving aim under the existence of movable (or in particular immovable) obstacles is considered in the report. This problem is represented as two-person zero-sum game, taking place in a metric space ..

厭惡

Conference proceedings 1996d papers. Also included are two comprehensive tutorial texts and an introduction by the volume editors. Thus the book is both a competent state-of-the-art report on current research and development and a valuable survey and introduction for researchers entering the area or professionals interested in the application of up-to-date techniques.

頭盔

Uncertainty reasoning in object recognition by image processing,ed to compute a match metric, in order to assess the quality of possible models. We discuss two methods for dealing with extracted uncertainty. Finally, we speculate on other methods of assessing uncertainty in the recognition process.

SEVER

皮薩

Mathematical foundations of navigation and perception for an autonomous mobile robot,formally sound method for combining internal and external sensor information from different sources, operating at different rates. The foundations of estimation theory are reviewed, and mathematical tools are derived for combining sensory information. In particular, a predict-match-update cycle is d

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