SE548113C2 - Robotic work tool with local map alignment and reinforcement learning-based coverage path planning - Google Patents

Robotic work tool with local map alignment and reinforcement learning-based coverage path planning

Info

Publication number
SE548113C2
SE548113C2 SE2350590A SE2350590A SE548113C2 SE 548113 C2 SE548113 C2 SE 548113C2 SE 2350590 A SE2350590 A SE 2350590A SE 2350590 A SE2350590 A SE 2350590A SE 548113 C2 SE548113 C2 SE 548113C2
Authority
SE
Sweden
Prior art keywords
path planning
work tool
reinforcement learning
local map
robotic work
Prior art date
Application number
SE2350590A
Other versions
SE2350590A1 (en
Inventor
Arvi Jonnarth
Michael Felsberg
Original Assignee
Husqvarna Ab
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Husqvarna Ab filed Critical Husqvarna Ab
Priority to SE2350590A priority Critical patent/SE548113C2/en
Priority to PCT/SE2024/050184 priority patent/WO2024237831A1/en
Publication of SE2350590A1 publication Critical patent/SE2350590A1/en
Publication of SE548113C2 publication Critical patent/SE548113C2/en

Links

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/60—Intended control result
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/20—Control system inputs
    • G05D1/24—Arrangements for determining position or orientation
    • G05D1/246—Arrangements for determining position or orientation using environment maps, e.g. simultaneous localisation and mapping [SLAM]
    • G05D1/2464—Arrangements for determining position or orientation using environment maps, e.g. simultaneous localisation and mapping [SLAM] using an occupancy grid
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01D—HARVESTING; MOWING
    • A01D34/00—Mowers; Mowing apparatus of harvesters
    • A01D34/006—Control or measuring arrangements
    • A01D34/008—Control or measuring arrangements for automated or remotely controlled operation
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/20—Control system inputs
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/40—Control within particular dimensions
    • G05D1/43—Control of position or course in two dimensions [2D]
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/60—Intended control result
    • G05D1/617—Safety or protection, e.g. defining protection zones around obstacles or avoiding hazards
    • G05D1/622—Obstacle avoidance
    • G05D1/633—Dynamic obstacles
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/60—Intended control result
    • G05D1/644—Optimisation of travel parameters, e.g. of energy consumption, journey time or distance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/60—Intended control result
    • G05D1/648—Performing a task within a working area or space, e.g. cleaning
    • G05D1/6482—Performing a task within a working area or space, e.g. cleaning by dividing the whole area or space in sectors to be processed separately
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/092—Reinforcement learning
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2101/00—Details of software or hardware architectures used for the control of position
    • G05D2101/10—Details of software or hardware architectures used for the control of position using artificial intelligence [AI] techniques
    • G05D2101/15—Details of software or hardware architectures used for the control of position using artificial intelligence [AI] techniques using machine learning, e.g. neural networks
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2105/00—Specific applications of the controlled vehicles
    • G05D2105/15—Specific applications of the controlled vehicles for harvesting, sowing or mowing in agriculture or forestry
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2107/00—Specific environments of the controlled vehicles
    • G05D2107/20—Land use
    • G05D2107/23—Gardens or lawns
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2109/00—Types of controlled vehicles
    • G05D2109/10—Land vehicles

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Theoretical Computer Science (AREA)
  • Software Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Mathematical Physics (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • General Health & Medical Sciences (AREA)
  • Computational Linguistics (AREA)
  • Biomedical Technology (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Environmental Sciences (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
SE2350590A 2023-05-16 2023-05-16 Robotic work tool with local map alignment and reinforcement learning-based coverage path planning SE548113C2 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
SE2350590A SE548113C2 (en) 2023-05-16 2023-05-16 Robotic work tool with local map alignment and reinforcement learning-based coverage path planning
PCT/SE2024/050184 WO2024237831A1 (en) 2023-05-16 2024-02-28 Improved navigation for a robotic work tool system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
SE2350590A SE548113C2 (en) 2023-05-16 2023-05-16 Robotic work tool with local map alignment and reinforcement learning-based coverage path planning

Publications (2)

Publication Number Publication Date
SE2350590A1 SE2350590A1 (en) 2024-11-17
SE548113C2 true SE548113C2 (en) 2026-03-30

Family

ID=90246054

Family Applications (1)

Application Number Title Priority Date Filing Date
SE2350590A SE548113C2 (en) 2023-05-16 2023-05-16 Robotic work tool with local map alignment and reinforcement learning-based coverage path planning

Country Status (2)

Country Link
SE (1) SE548113C2 (en)
WO (1) WO2024237831A1 (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN120722837B (en) * 2025-08-15 2025-11-04 苏州大学 Complex curved surface turning processing path planning method based on map measurement

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190094870A1 (en) * 2014-12-16 2019-03-28 AI Incorporated Methods and systems for robotic surface coverage
US20190101917A1 (en) * 2017-10-04 2019-04-04 Hengshuai Yao Method of selection of an action for an object using a neural network
WO2020062911A1 (en) * 2018-09-26 2020-04-02 Huawei Technologies Co., Ltd. Actor ensemble for continuous control
US20200166896A1 (en) * 2018-11-26 2020-05-28 Uber Technologies, Inc. Deep reinforcement learning based models for hard-exploration problems
US20200167686A1 (en) * 2018-11-27 2020-05-28 Amazon Technologies, Inc. Reinforcement learning model training through simulation
US20200234117A1 (en) * 2017-08-25 2020-07-23 Google Llc Batched reinforcement learning
US20220026920A1 (en) * 2020-06-10 2022-01-27 AI Incorporated Light weight and real time slam for robots
US20220066456A1 (en) * 2016-02-29 2022-03-03 AI Incorporated Obstacle recognition method for autonomous robots
US11481918B1 (en) * 2017-07-27 2022-10-25 AI Incorporated Method and apparatus for combining data to construct a floor plan
CN115826581A (en) * 2022-12-28 2023-03-21 大连大学 Mobile robot path planning algorithm combining fuzzy control and reinforcement learning

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20220046210A (en) * 2020-10-07 2022-04-14 엘지전자 주식회사 Mobile robot and control method thereof

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190094870A1 (en) * 2014-12-16 2019-03-28 AI Incorporated Methods and systems for robotic surface coverage
US20220066456A1 (en) * 2016-02-29 2022-03-03 AI Incorporated Obstacle recognition method for autonomous robots
US11481918B1 (en) * 2017-07-27 2022-10-25 AI Incorporated Method and apparatus for combining data to construct a floor plan
US20200234117A1 (en) * 2017-08-25 2020-07-23 Google Llc Batched reinforcement learning
US20190101917A1 (en) * 2017-10-04 2019-04-04 Hengshuai Yao Method of selection of an action for an object using a neural network
WO2020062911A1 (en) * 2018-09-26 2020-04-02 Huawei Technologies Co., Ltd. Actor ensemble for continuous control
US20200166896A1 (en) * 2018-11-26 2020-05-28 Uber Technologies, Inc. Deep reinforcement learning based models for hard-exploration problems
US20200167686A1 (en) * 2018-11-27 2020-05-28 Amazon Technologies, Inc. Reinforcement learning model training through simulation
US20220026920A1 (en) * 2020-06-10 2022-01-27 AI Incorporated Light weight and real time slam for robots
CN115826581A (en) * 2022-12-28 2023-03-21 大连大学 Mobile robot path planning algorithm combining fuzzy control and reinforcement learning

Also Published As

Publication number Publication date
SE2350590A1 (en) 2024-11-17
WO2024237831A1 (en) 2024-11-21

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