Commissariat &#xc0; L'&#xc9;nergie Atomique Et Aux &#xc9;nergies Alternatives

Frédéric Heitzmann

Suzanne Lesecq

Edith Beigne

Diego Puschini Pascual

Julien Mottin

Tiana Rakotovao Andriamahefa

Olivier Debicki

Roxana Dia

Olivier Sentieys

Florent Berthier

Christmann Jean-Frédéric

An environment sensing method includes the following steps, carried out by a data processor a) defining an occupancy grid comprising a plurality of cells; b) acquiring at least one measurement result from a distance sensor, representative of the distance of one or more nearest targets; and c) computing an occupation probability of the cells of the occupancy grid by applying to the measurement an inverse sensor model stored in a memory device in the form of a data structure representing a plurality of model grids associated to respective distance measurement results, at least some cells of a model grid corresponding to a plurality of contiguous cells of the occupancy grid belonging to a same of a plurality of angular sectors into which the field of view of the distance sensor is divided, and associating a same occupation probability to each one of the plurality of cells. An apparatus programmed or configured for carrying out the environment sensing method and a computer-implemented method of computing an inverse sensor model suitable for carrying out the environment sensing method are also provided.

Environment sensing method and apparatus using a wide-angle distance sensor

A method for perceiving physical bodies comprises the following steps: a) acquisition of a plurality of distance measurements of the physical bodies arising from one or more sensors; b) acquisition or computation of a value of a priori probability of occupancy of the cells of an occupancy grid; and c) application of an inverse sensor model on the occupancy grid to determine a probability of occupancy of a set of cells of the grid; d) construction of a consolidated occupancy grid by fusing the occupancy probabilities estimated during step c); wherein each the inverse sensor model is a discrete model, associating with each cell of the corresponding occupancy grid, and for each distance measurement, a probability class chosen inside one and the same set of finite cardinality and identified by an integer index; and wherein step d) is implemented by means of integer computations performed on the indices of the probability classes determined during step c), and as a function of the value of a priori occupancy probability. A system for perceiving physical bodies, adapted to implement the method is provided.

Method and system for contextualized perception of physical bodies

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Grenoble, France

Frédéric Heitzmann