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See all Premium member Presentation Transcript EE631 Cooperating Autonomous Mobile RobotsLecture 5: Collision Avoidance in Dynamic Environments: EE631 Cooperating Autonomous Mobile Robots Lecture 5: Collision Avoidance in Dynamic Environments Prof. Yi Guo ECE Dept.Plan: Plan A Collision Avoidance Algorithm A Global Motion Planning SchemeNonholonomic Kinematic Model: Nonholonomic Kinematic Model Coordinate transformation and input mapping (, are within (-/2,/2)): Chained form (after transformation):Assumptions: The Robot: Assumptions: The Robot 2-dimensional circle with radius R Knowing its start and goal positions Onboard sensors detecting dynamic obstaclesAssumptions: The Environment: Assumptions: The Environment 2D environment with static and dynamic obstacles Pre-defined map with static obstacle locations known Dynamic obstacles represented by circles with radius riProblem Formulation: Trajectory Planning: Problem Formulation: Trajectory Planning Find feasible trajectories for the robot, enrouting from its start position to its goal, without collisions with static and dynamic obstacles. Feasible Trajectory in Free Space: Feasible Trajectory in Free Space A family of feasible trajectories: Boundary conditions In original coordinate: In transformed coordinate:Parameterized Feasible Trajectory: Parameterized Feasible Trajectory Imposing boundary conditions, parameterization of the trajectory in terms of a6: A, B, Y are constant matrices calculated from boundary conditions a6 increases the freedom of maneuver accounting for geometric constrains posed by dynamic obstacles Steering Paradigm: Steering Paradigm Polynomial steering: Assume T is the time that takes the robot to get to qf from q0. Choose thenA quick summary: A quick summary System model: chained form Feasible trajectories: closed form parameterization Steering control: closed form, piecewise constant solution (polynomial steering) Next: Collision avoidance -- explicit condition based on geometry and timeDynamic Collision Avoidance Criteria: Dynamic Collision Avoidance Criteria Time + space collisionDynamic Collision Avoidance Criteria: Dynamic Collision Avoidance Criteria Time criterion: Assume obstacle moves at constant velocity during sampling period In original coordinate: In transformed coordinate : Dynamic Collision Avoidance Criteria: Dynamic Collision Avoidance Criteria Geometry criterion: In original coordinate: In transformed coordinate: Mapping from x-y plane to z1-z4 plane indicates collision region within a circle of radius ri+R+l/2, sinceDynamic Collision Avoidance Criteria: Dynamic Collision Avoidance Criteria Time criterion + geometrical criterion + path parameterization g2, g1i, g0i are analytic functions of their arguments and can be calculated real time a6k exists if g2>0 g2>0 holds for every points except boundary pointsGlobal Path Planning Using D* Search: Global Path Planning Using D* Search A shortest path returned by D* in 2D environment Global Motion Planning: Global Motion Planning Algorithm flow chartSimulations: Simulations In 2D environment with static obstacles (a6=0) Collision Trajectory: Collision Trajectory Circles are drawn with 5 second spacing Onboard sensors detect: obstacle 1: center [23,15], velocity [0.1,0.2] obstacle 2: center [45,20], velocity [-0.1,-0.1] Collisions occursGlobal Collision–Free Trajectory: Global Collision–Free Trajectory a61=9.4086*10-6, a62=4.9973*10-6Global Collision–Free Trajectory: Global Collision–Free Trajectory Moving obstacle changes velocity: Original velocity [-0.15,-0.1], new velocity [0.15,-0.29] Calculated a62=9.4086*10-6, a62=4.9973*10-6Readings:: Readings: Laumond book Chapter 1 “A new analytical solution to mobile robot trajectory generation in the presence of moving obstacles”, by Zhihua Qu, Jing Wang, Plaisted, C.E., IEEE Transactions on Robotics, Volume 20, Issue 6, Dec. 2004 Page(s):978 - 993 You do not have the permission to view this presentation. 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Collision Avoidance Oceane 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: 405 Category: Entertainment License: All Rights Reserved Like it (0) Dislike it (0) Added: December 31, 2007 This Presentation is Public Favorites: 0 Presentation Description No description available. Comments Posting comment... By: lucky001.0706 (13 month(s) ago) ma chuda bhosdike ..................fuck u .................. Saving..... Post Reply Close Saving..... Edit Comment Close By: lucky001.0706 (13 month(s) ago) ma chuda bhosdike ..................fuck u .................. Saving..... Post Reply Close Saving..... 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See all Premium member Presentation Transcript EE631 Cooperating Autonomous Mobile RobotsLecture 5: Collision Avoidance in Dynamic Environments: EE631 Cooperating Autonomous Mobile Robots Lecture 5: Collision Avoidance in Dynamic Environments Prof. Yi Guo ECE Dept.Plan: Plan A Collision Avoidance Algorithm A Global Motion Planning SchemeNonholonomic Kinematic Model: Nonholonomic Kinematic Model Coordinate transformation and input mapping (, are within (-/2,/2)): Chained form (after transformation):Assumptions: The Robot: Assumptions: The Robot 2-dimensional circle with radius R Knowing its start and goal positions Onboard sensors detecting dynamic obstaclesAssumptions: The Environment: Assumptions: The Environment 2D environment with static and dynamic obstacles Pre-defined map with static obstacle locations known Dynamic obstacles represented by circles with radius riProblem Formulation: Trajectory Planning: Problem Formulation: Trajectory Planning Find feasible trajectories for the robot, enrouting from its start position to its goal, without collisions with static and dynamic obstacles. Feasible Trajectory in Free Space: Feasible Trajectory in Free Space A family of feasible trajectories: Boundary conditions In original coordinate: In transformed coordinate:Parameterized Feasible Trajectory: Parameterized Feasible Trajectory Imposing boundary conditions, parameterization of the trajectory in terms of a6: A, B, Y are constant matrices calculated from boundary conditions a6 increases the freedom of maneuver accounting for geometric constrains posed by dynamic obstacles Steering Paradigm: Steering Paradigm Polynomial steering: Assume T is the time that takes the robot to get to qf from q0. Choose thenA quick summary: A quick summary System model: chained form Feasible trajectories: closed form parameterization Steering control: closed form, piecewise constant solution (polynomial steering) Next: Collision avoidance -- explicit condition based on geometry and timeDynamic Collision Avoidance Criteria: Dynamic Collision Avoidance Criteria Time + space collisionDynamic Collision Avoidance Criteria: Dynamic Collision Avoidance Criteria Time criterion: Assume obstacle moves at constant velocity during sampling period In original coordinate: In transformed coordinate : Dynamic Collision Avoidance Criteria: Dynamic Collision Avoidance Criteria Geometry criterion: In original coordinate: In transformed coordinate: Mapping from x-y plane to z1-z4 plane indicates collision region within a circle of radius ri+R+l/2, sinceDynamic Collision Avoidance Criteria: Dynamic Collision Avoidance Criteria Time criterion + geometrical criterion + path parameterization g2, g1i, g0i are analytic functions of their arguments and can be calculated real time a6k exists if g2>0 g2>0 holds for every points except boundary pointsGlobal Path Planning Using D* Search: Global Path Planning Using D* Search A shortest path returned by D* in 2D environment Global Motion Planning: Global Motion Planning Algorithm flow chartSimulations: Simulations In 2D environment with static obstacles (a6=0) Collision Trajectory: Collision Trajectory Circles are drawn with 5 second spacing Onboard sensors detect: obstacle 1: center [23,15], velocity [0.1,0.2] obstacle 2: center [45,20], velocity [-0.1,-0.1] Collisions occursGlobal Collision–Free Trajectory: Global Collision–Free Trajectory a61=9.4086*10-6, a62=4.9973*10-6Global Collision–Free Trajectory: Global Collision–Free Trajectory Moving obstacle changes velocity: Original velocity [-0.15,-0.1], new velocity [0.15,-0.29] Calculated a62=9.4086*10-6, a62=4.9973*10-6Readings:: Readings: Laumond book Chapter 1 “A new analytical solution to mobile robot trajectory generation in the presence of moving obstacles”, by Zhihua Qu, Jing Wang, Plaisted, C.E., IEEE Transactions on Robotics, Volume 20, Issue 6, Dec. 2004 Page(s):978 - 993