logging in or signing up 3d mapping Isab Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 993 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: January 04, 2008 This Presentation is Public Favorites: 1 Presentation Description No description available. Comments Posting comment... By: bsandeepthigoud (11 month(s) ago) guddddd Saving..... Post Reply Close Saving..... Edit Comment Close Premium member Presentation Transcript 3D Mapping Robots: 3D Mapping Robots Intelligent Robotics School of Computer Science Jeremy Wyatt James Walker What Are 3D Mapping Robots and Their Uses?: What Are 3D Mapping Robots and Their Uses? Robots which produce a 3-dimensional model of their environment from the data they collect They can be used by people who need to know more about the interior of a building: Architects Fire fighters Human rescue workersTypes of Sensing Techniques: Types of Sensing Techniques Stereo vision Laser range finders A combination of the twoStereo Vision: Stereo Vision Use stereo disparities to compute depth Inaccurate in detecting the position of walls and objects especially in cluttered environmentsLaser Range Finders: Laser Range Finders Very accurate in measuring distances to walls and objects in the environment Has a range of 8m with a resolution of 1mm and a statistical error of +/-10mm Can not detect any texture in the environment so can only produce single coloured modelsA Combination of the Two: A Combination of the Two Laser range finders for detecting the distance of walls and objects An omni-cam for producing texture maps for a realistic visualisation of the environmentThe GATech Robot: The GATech Robot Equipped with a laser range finder positioned vertically to scan perpendicular to the movement of the robotHow the Robot Builds the 3D Models: How the Robot Builds the 3D Models Collects raw data from the environment using the laser range finder Converts the raw data into Cartesian co-ordinates Converts the Cartesian co-ordinates into a mesh for the 3D modelHow the Robot Collects the Raw Data: How the Robot Collects the Raw Data Laser moves through 180˚ in 0.5˚ steps from one side of the robot over the top to the other recording the distance Approximately 38 scans are completed every second Robot moves forward at 0.25m/s Therefore approximately one scan every 5cmTransforming the Raw Data Into Co-ordinates: Transforming the Raw Data Into Co-ordinates Raw data is in the form of cylindrical co-ordinates Transformed using the pose of the robot, the angle of the scan and the height of the centre of the laser scannerCollecting the Co-ordinates to Form Triangles: Collecting the Co-ordinates to Form Triangles Choose two scan points p1 and p2 from the same scan, taken at angles α and α + 0.5˚ Choose the two corresponding points q1 and q2 from the next scan Form two triangles p1p2q1 and q1p2q2 For each triangle calculate its normal vector GATech Model: GATech ModelGATech Model: GATech ModelGATech Model: GATech ModelDisadvantages of This Approach: Disadvantages of This Approach The corridor appears to be slightly curved due to the way the robot moves Obstacles below a height of 0.52m can not be detected by the robot No filtering techniques were used so the model is very noisy but retains a high level of complexity because of thisFurther Examples: Thrun et al: Further Examples: Thrun et al Uses two laser range finders and an omni-cam Uses a technique called expectation maximisation Processes the data to reduce the noiseExpectation Maximisation: Expectation Maximisation Estimates the number of surfaces and their location Adds and removes surfaces until it converges on the best fit model for the dataThrun et al: Thrun et alThrun et al: Thrun et alSummary: Summary Brief overview of what 3D mapping is and some uses for 3D mapping Different types of sensors used How to collect data and convert it into a 3D model Some more advanced methods for 3D mapping and processing of the dataReferences: References www.cc.gatech.edu/ai/robot-lab/research/3d/ www-2.cs.cmu.edu/~thrun/3d/Processing the Data: Processing the Data Various techniques and algorithms have been used to reduce the noise in the data Smoothing is always used as a final post processing step as nearby measurements are likely to belong to the same surfaceTypes of 3D Mapping Robots: Types of 3D Mapping Robots Stationary Move with manual guidance Fully automated You do not have the permission to view this presentation. In order to view it, please contact the author of the presentation.
3d mapping Isab Download Post to : URL : Related Presentations : Share Add to Flag Embed Email Send to Blogs and Networks Add to Channel Uploaded from authorPOINTLite Insert YouTube videos in PowerPont slides with aS Desktop Copy embed code: (To copy code, click on the text box) Embed: URL: Thumbnail: WordPress Embed Customize Embed The presentation is successfully added In Your Favorites. Views: 993 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: January 04, 2008 This Presentation is Public Favorites: 1 Presentation Description No description available. Comments Posting comment... By: bsandeepthigoud (11 month(s) ago) guddddd Saving..... Post Reply Close Saving..... Edit Comment Close Premium member Presentation Transcript 3D Mapping Robots: 3D Mapping Robots Intelligent Robotics School of Computer Science Jeremy Wyatt James Walker What Are 3D Mapping Robots and Their Uses?: What Are 3D Mapping Robots and Their Uses? Robots which produce a 3-dimensional model of their environment from the data they collect They can be used by people who need to know more about the interior of a building: Architects Fire fighters Human rescue workersTypes of Sensing Techniques: Types of Sensing Techniques Stereo vision Laser range finders A combination of the twoStereo Vision: Stereo Vision Use stereo disparities to compute depth Inaccurate in detecting the position of walls and objects especially in cluttered environmentsLaser Range Finders: Laser Range Finders Very accurate in measuring distances to walls and objects in the environment Has a range of 8m with a resolution of 1mm and a statistical error of +/-10mm Can not detect any texture in the environment so can only produce single coloured modelsA Combination of the Two: A Combination of the Two Laser range finders for detecting the distance of walls and objects An omni-cam for producing texture maps for a realistic visualisation of the environmentThe GATech Robot: The GATech Robot Equipped with a laser range finder positioned vertically to scan perpendicular to the movement of the robotHow the Robot Builds the 3D Models: How the Robot Builds the 3D Models Collects raw data from the environment using the laser range finder Converts the raw data into Cartesian co-ordinates Converts the Cartesian co-ordinates into a mesh for the 3D modelHow the Robot Collects the Raw Data: How the Robot Collects the Raw Data Laser moves through 180˚ in 0.5˚ steps from one side of the robot over the top to the other recording the distance Approximately 38 scans are completed every second Robot moves forward at 0.25m/s Therefore approximately one scan every 5cmTransforming the Raw Data Into Co-ordinates: Transforming the Raw Data Into Co-ordinates Raw data is in the form of cylindrical co-ordinates Transformed using the pose of the robot, the angle of the scan and the height of the centre of the laser scannerCollecting the Co-ordinates to Form Triangles: Collecting the Co-ordinates to Form Triangles Choose two scan points p1 and p2 from the same scan, taken at angles α and α + 0.5˚ Choose the two corresponding points q1 and q2 from the next scan Form two triangles p1p2q1 and q1p2q2 For each triangle calculate its normal vector GATech Model: GATech ModelGATech Model: GATech ModelGATech Model: GATech ModelDisadvantages of This Approach: Disadvantages of This Approach The corridor appears to be slightly curved due to the way the robot moves Obstacles below a height of 0.52m can not be detected by the robot No filtering techniques were used so the model is very noisy but retains a high level of complexity because of thisFurther Examples: Thrun et al: Further Examples: Thrun et al Uses two laser range finders and an omni-cam Uses a technique called expectation maximisation Processes the data to reduce the noiseExpectation Maximisation: Expectation Maximisation Estimates the number of surfaces and their location Adds and removes surfaces until it converges on the best fit model for the dataThrun et al: Thrun et alThrun et al: Thrun et alSummary: Summary Brief overview of what 3D mapping is and some uses for 3D mapping Different types of sensors used How to collect data and convert it into a 3D model Some more advanced methods for 3D mapping and processing of the dataReferences: References www.cc.gatech.edu/ai/robot-lab/research/3d/ www-2.cs.cmu.edu/~thrun/3d/Processing the Data: Processing the Data Various techniques and algorithms have been used to reduce the noise in the data Smoothing is always used as a final post processing step as nearby measurements are likely to belong to the same surfaceTypes of 3D Mapping Robots: Types of 3D Mapping Robots Stationary Move with manual guidance Fully automated