Abstract: The present invention relates to a method for managing an automatic warehouse and for locating a mobile target, such as a person or a manual guided vehicle (1).

Abstract: The movement of a part of human body, e.g. a limb, is monitored. The movement includes N iterated rotations in a plane. A sensing device is fixed to the limb and provides data indicative of the limb movement. These data are processed to generate a rotation signal. Then, portions of the rotation signal corresponding to each movement iteration are identified. To this purpose, a plurality of null-velocity instants is identified, wherein the angular velocity of the sensing device is null. Then, each null-velocity instant is classified as a candidate start/end time or a candidate peak time. Then, a start time, end time and peak time for each iteration are determined as a combination of two candidate start/end times and a candidate peak time that fulfils certain conditions on the values of the rotation signal in correspondence of candidate start/end times and candidate peak times.

Abstract: The present invention relates to a localization or position estimation group for a moving target, such as a person or a manual guided vehicle, in a warehouse or in an area to be monitored with at least one automatic guided vehicle, equipped with a unit for controlling the movement of the automatic guided vehicle itself, and at least one moving target.

Abstract: The movement of a part of human body, e.g. a limb, is monitored. The movement includes N iterated rotations in a plane. A sensing device is fixed to the limb and provides data indicative of the limb movement. These data are processed to generate a rotation signal. Then, portions of the rotation signal corresponding to each movement iteration are identified. To this purpose, a plurality of null-velocity instants is identified, wherein the angular velocity of the sensing device is null. Then, each null-velocity instant is classified as a candidate start/end time or a candidate peak time. Then, a start time, end time and peak time for each iteration are determined as a combination of two candidate start/end times and a candidate peak time that fulfils certain conditions on the values of the rotation signal in correspondence of candidate start/end times and candidate peak times.

Abstract: The present invention relates to a localisation or estimation group of the position of a moving target, such as a person or a manual guided vehicle, in a warehouse or in an area to be monitored with at least one automatic guided vehicle, equipped with a unit for controlling the movement of the automatic guided vehicle itself, and at least a moving target.

Abstract: The method for configuring a network of deposited wireless sensors. In certain aspects, these methods include defining performance criteria forming constraints, with associated threshold values, and at least one performance criterion to be optimized, for at least one zone to be equipped with nodes, each performance criterion being defined by a model; defining for said or each zone; the allocation to said or each zone to be equipped, a number of nodes; applying an optimization process per zone on said or each zone; increasing the number of nodes or modifying the performance criteria defined in said or each zone where the performance criteria are not met and reproducing in these zones the optimization process per zone with the new number of nodes or the new performance criteria, and applying the configuration determined at each node in said or each zone.

Abstract: The method for configuring a network of deposited wireless sensors. In certain aspects, these methods include defining performance criteria forming constraints, with associated threshold values, and at least one performance criterion to be optimized, for at least one zone to be equipped with nodes, each performance criterion being defined by a model; defining for said or each zone; the allocation to said or each zone to be equipped, a number of nodes; applying an optimization process per zone on said or each zone; increasing the number of nodes or modifying the performance criteria defined in said or each zone where the performance criteria are not met and reproducing in these zones the optimization process per zone with the new number of nodes or the new performance criteria, and applying the configuration determined at each node in said or each zone.