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EE631 Cooperating Autonomous Mobile Robots Lecture: Collision Avoidance in Dynamic Environments Prof. Yi Guo ECE Dept.

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Presentation on theme: "EE631 Cooperating Autonomous Mobile Robots Lecture: Collision Avoidance in Dynamic Environments Prof. Yi Guo ECE Dept."— Presentation transcript:

1 EE631 Cooperating Autonomous Mobile Robots Lecture: Collision Avoidance in Dynamic Environments
Prof. Yi Guo ECE Dept.

2 Plan A Collision Avoidance Algorithm A Global Motion Planning Scheme

3 Nonholonomic Kinematic Model
Coordinate transformation and input mapping (, are within (-/2,/2)): Chained form (after transformation):

4 Assumptions: The Robot
2-dimensional circle with radius R Knowing its start and goal positions Onboard sensors detecting dynamic obstacles

5 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 ri

6 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.

7 Feasible Trajectory in Free Space
A family of feasible trajectories: Boundary conditions In original coordinate: In transformed coordinate:

8 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

9

10 Steering Paradigm Polynomial steering:
Assume T is the time that takes the robot to get to qf from q0. Choose then

11 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 time

12 Dynamic Collision Avoidance Criteria
Time + space collision

13 Dynamic Collision Avoidance Criteria
Time criterion: Assume obstacle moves at constant velocity during sampling period In original coordinate: In transformed coordinate :

14 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, since

15 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 points

16 Global Path Planning Using D* Search
Robot path Static obstacles Start Goal A shortest path returned by D* in 2D environment

17 Global Motion Planning
Algorithm flow chart

18 In 2D environment with static obstacles (a6=0)
Simulations Static obstacles Feasible trajectory Start Goal In 2D environment with static obstacles (a6=0)

19 Collision Trajectory Circles are drawn with 5 second spacing
Moving obstacles Robot Static obstacles 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 occurs

20 Global Collision–Free Trajectory
Moving obstacles Robot Static obstacles a61=9.4086*10-6, a62=4.9973*10-6

21 Global Collision–Free Trajectory
Moving obstacles Robot Static obstacles 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*10-6

22 Readings: “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 Page(s):


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