Husqvarna Ab

Stefan Grufman

Björn Mannefred

Magnus Öhrlund

Patrik Jägenstedt

Fredrik Kallström

Mattias Kamfors

Mikael Willgert

Anders Mattsson

Marcus Liljedahl

Tommy Glimberg

Beppe Hellsin

Eric Lennings

Peter Reigo

Jonas Holgersson

Fredrik Edholm

Tomas Wykman

Olle Markusson

Johan Deimert

Pär Christensson

Lars Dernebo

Martin Larsén

Andreas Källming

Hans Forsberg

Jonas Rangsjö

Fredrik Klackensjö

Jonas Agerhall

Kent Askenmalm

Stefan Bergström

Peter Lameli

Christoph Schiedt

Mikael Alexiusson

Åke Cederborn

Erik Starhagen

Claes Johannesson

Marcus Stjärnås

Hugo Johansson

Göran Calás

Sven Wietelmann

Göran Calås

Beppe Hesssin

Jonas RangsjÖ

A robotic work tool system () comprising a robotic work tool () comprising a controller (), the controller () being configured to determine an area locality () associated with a hindrance; determine a classifier (C) associated with the area locality (); and determine an action for the robotic work tool (), wherein the action is based on the classifier (C).

Navigation for a robotic work tool

A robotic work tool system () comprising a robotic work tool (), the robotic work tool () being configured to determine () that the robotic work tool () has entered a state of limited movement; determine () an exit path; and exit () the state of limited movement by navigating the exit path.

Exit path determination for a robotic work tool

A robotic work tool system () for defining a working area () in which a robotic work tool () is subsequently intended to operate. The robotic work tool system () comprises a robotic work tool (), at least one controller () and at least one memory (). The robotic work tool () comprises at least one sensor unit () configured to collect sensed input data while the robotic work tool () is driven around the working area () to preliminarily define a perimeter around the working area (). The at least one controller () is configured to establish a preliminary working area perimeter (). The at least one memory () is configured to store a perimeter adjustment function and instructions that cause the at least one controller () to adjust the perimeter of the working area () by applying the stored perimeter adjustment function to the established preliminary working area perimeter () and thereby produce an adjusted working area perimeter (). The perimeter adjustment function is based on the collected sensed input data corresponding to terrain features.

Robotic work tool system and method for defining a working area

A robotic work tool system () for avoiding trails from a robotic work tool () in a transit zone () in which the robotic work tool () is allowed to travel from a start point () to a goal point () along a travel path (). The system () comprises at least one memory () configured to store information about the transit zone (), at least one robotic work tool () configured to travel along the travel path () and at least one controller () for controlling operation of the robotic work tool (). The controller () is configured to receive, from the memory (), information about the transit zone () and generate, based on the transit zone (), the travel path () for the robotic work tool () from the start point () to the goal point (). The generated travel path () is configured to differ from previously generated travel paths.

Robotic work tool system and method for transporting a robotic work tool between different areas

Some example embodiments may provide a capability for intelligent control or management of a number of assets in connection with yard maintenance with the assistance or inclusion of a management unit having distributed properties. Thus, for example, sensor equipment and task performance equipment operation may be coordinated between local management and remote management entities for efficient monitoring and maintaining of lawn wellness.

Lawn monitoring and maintenance via a robotic vehicle

The present disclosure relates to a self-propelled robotic tool () and a method in a self-propelled robotic tool (), being used to detecting lifting of the self-propelled robotic device from the ground. The method includes collecting () driving data () related to the driving of a wheel (), collecting () measured inertia data from an inertial measurement unit (), IMU, in the self-propelled robotic tool, determining (), using an estimation function (), a residual parameter corresponding to a differential between said measured inertia data and estimated inertia data resulting from said driving data being input to said estimation function, and determining a lifting condition based on the residual parameter.

Method for detecting lifting of a self-propelled tool from the ground

A method for robotic discovery and use of beacons for navigation may include performing a beacon position determination process with respect to at least one beacon usable for range determination by a robotic vehicle responsive to initiation of operation of the robotic vehicle. The method may further include determining a position of the at least one beacon based on the position determination process, and employing the position of the at least one beacon as determined for position information determination of the robotic vehicle during continued operation of the robotic vehicle.

Automatic beacon position determination

A robotic vehicle may be configured to incorporate multiple sensors to make the robotic vehicle capable of collecting, feeding, and uploading weather data into an aggregation agent to form a geospatial map or weather service. In this regard, in some cases, the robotic vehicle may include an onboard vehicle positioning module and sensor network to give the robotic vehicle a collective understanding of its environment, and enable it to autonomously collect and upload weather data to an aggregation agent for corresponding locations.

Weather collection and aggregation via robotic vehicle

A method of navigating a self-propelled robotic tool comprises transmitting a wireless signal () along a first signal path between the robotic tool () and a first wireless interface of a base station () remote from the robotic tool (); transmitting a wireless signal () along a second signal path between the robotic tool () and a second wireless interface of the base station (), said second wireless interface being spatially separated from the first wireless interface by a separation distance; upon receipt, comparing the signal transmitted along the first signal path with the signal transmitted along the second signal path to obtain a propagation time difference between the signal transmitted along the first signal path and the signal transmitted along the second signal path, said propagation time difference defining a path length difference between said first and second signal paths; and calculating, based on the separation distance and the path length difference, a value representative of a bearing (&#x3c6;) from the base station () to the robotic tool ().

Self-propelled robotic tool navigation

A robotic vehicle may include one or more functional components configured to execute a lawn care function, a sensor network comprising one or more sensors configured to detect conditions proximate to the robotic vehicle, an object detection module configured to 5 detect objects proximate to the robotic vehicle using contact-less detection, a positioning module configured to determine robotic vehicle position, and a mapping module configured to generate map data regarding a parcel on which the robotic vehicle operates.

Multi-sensor, autonomous robotic vehicle with lawn care function

A robotic vehicle may be configured to incorporate multiple sensors to make the robotic vehicle capable of collecting and uploading image data over time into the cloud to generate interactive garden models. In this regard, in some cases, the robotic vehicle may include an onboard vehicle positioning module and sensor network that may work together to give the robotic vehicle a collective understanding of its environment, and enable it to autonomously collect and upload image data for corresponding locations.

Garden street view

A method for mapping and planning a parcel or garden may include receiving information indicative of position data of a robotic vehicle transiting a parcel and corresponding image data captured by the robotic vehicle at one or more locations on the parcel. The method may further include generating a base-map of the parcel based on the information received and providing a graphical representation of the parcel based on the base-map. The method may further include enabling an operator to generate a modified-map.

Garden mapping and planning via robotic vehicle

A robotic work tool () comprising an altitude sensor () for providing a current altitude reading (HRL) and a controller () configured to receive the current altitude reading (HRL) from the altitude sensor (); determine an altitude (H) based on the current altitude reading (HRL); determine a current position; and generating a map indicating elevations by including the determined altitude (H) for the current position in the map. A robotic work tool system () comprising a robotic work tool () and a reference altitude sensor () for providing a reference altitude reading (HCS), wherein the robotic work tool () is further configured to receive the reference altitude reading (HCS) from the reference altitude sensor (); and determine the altitude (H) based on the current altitude reading (HRL) and the reference altitude reading (HCS).

3D map generation by a robotic work tool

A method for creating a visualization of a parcel or garden may include receiving information indicative of position data of a robotic vehicle transiting a parcel and corresponding image data captured by the robotic vehicle at one or more locations on the parcel. The method may further include generating a model of the parcel based on the information received, providing a graphical representation of the parcel based on the model, and enabling an operator to interact with the graphical representation to view one or more content items associated with respective ones of the one or more locations.

Garden visualization and mapping via robotic vehicle

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Bankeryd, Sweden

Stefan Grufman