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Introduction to Mobile Robotics Wheeled Locomotion Wolfram Burgard, Cyrill Stachniss, Maren Bennewitz, Kai Arras 1 Locomotion of Wheeled Robots Locomotion (Oxford Dict.): Power of motion from place to place Differential drive


  1. Introduction to Mobile Robotics Wheeled Locomotion Wolfram Burgard, Cyrill Stachniss, Maren Bennewitz, Kai Arras 1

  2. Locomotion of Wheeled Robots Locomotion (Oxford Dict.): Power of motion from place to place § Differential drive (AmigoBot, Pioneer 2-DX) § Car drive (Ackerman steering) § Synchronous drive (B21) § XR4000 § Mecanum wheels roll x y y z motion we also allow wheels to rotate around the z axis 2

  3. Instantaneous Center of Curvature ICC § For rolling motion to occur, each wheel has to move along its y-axis 3

  4. Differential Drive y ICC [ x R sin , y R cos ] = − θ + θ ICC ω v l ( R l / 2 ) v ω + = r ( R l / 2 ) v ω − = l θ R x l ( v v ) (x,y) + l r R = 2 ( v v ) − r l v r v v − l /2 r l ω = l 4

  5. Differential Drive: Forward Kinematics ICC x ' cos( t ) sin( t ) 0 x ICC ICC ωδ − ωδ − ⎡ ⎤ ⎡ ⎤ ⎡ ⎤ ⎡ ⎤ x x ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ y ' sin( t ) cos( t ) 0 y ICC ICC = ωδ ωδ − + y y ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ' 0 0 1 t ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ θ θ ωδ ⎣ ⎦ ⎣ ⎦ ⎣ ⎦ ⎣ ⎦ R t x ( t ) v ( t ' ) cos[ ( t ' )] dt ' = ∫ θ P(t+ δ t) 0 t y ( t ) v ( t ' ) sin[ ( t ' )] dt ' = ∫ θ 0 P(t) t ( t ) ( t ' ) dt ' θ = ∫ ω 0 5

  6. Differential Drive: Forward Kinematics ICC x ' cos( t ) sin( t ) 0 x ICC ICC ωδ − ωδ − ⎡ ⎤ ⎡ ⎤ ⎡ ⎤ ⎡ ⎤ x x ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ y ' sin( t ) cos( t ) 0 y ICC ICC = ωδ ωδ − + y y ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ' 0 0 1 t ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ ⎢ ⎥ θ θ ωδ ⎣ ⎦ ⎣ ⎦ ⎣ ⎦ ⎣ ⎦ R t 1 x ( t ) [ v ( t ' ) v ( t ' )] cos[ ( t ' )] dt ' P(t+ δ t) = ∫ + θ r l 2 0 t 1 y ( t ) [ v ( t ' ) v ( t ' )] sin[ ( t ' )] dt ' = ∫ + θ r l 2 0 t 1 P(t) ( t ) [ v ( t ' ) v ( t ' )] dt ' θ = ∫ − r l l 0 6

  7. Ackermann Drive ICC [ x R sin , y R cos ] = − θ + θ d R = y tan ϕ ω ϕ ( R l / 2 ) v ϕ ω + = ICC v r l ( R l / 2 ) v ω − = l l ( v v ) + l r R = θ R d 2 ( v v ) x − (x,y) r l v v − r l ω = v r l l /2 7

  8. Synchonous Drive y t x ( t ) v ( t ' ) cos[ ( t ' )] dt ' = ∫ θ 0 t y ( t ) v ( t ' ) sin[ ( t ' )] dt ' = ∫ θ v(t) θ 0 t x ( t ) ( t ' ) dt ' θ = ∫ ω ω ( ) t 0 8

  9. t XR4000 Drive x ( t ) v ( t ' ) cos[ ( t ' )] dt ' = ∫ θ 0 y t y ( t ) v ( t ' ) sin[ ( t ' )] dt ' = ∫ θ 0 t ( t ) ( t ' ) dt ' θ = ω ∫ v i (t) 0 θ x ω i (t) ICC 9

  10. Mecanum Wheels v ( v v v v ) / 4 = + + + y 0 1 2 3 v ( v v v v ) / 4 = − + − x 0 1 2 3 v ( v v v v ) / 4 = + − − 0 1 2 3 θ v ( v v v v ) / 4 = − − + error 0 1 2 3 11

  11. Example: Priamos (Karlsruhe) 12

  12. Example: KUKA youBot 14

  13. Example: Segway Omni 15

  14. Tracked Vehicles 16

  15. Other Robots: OmniTread [courtesy by Johann Borenstein] 17

  16. Other Robots: Humanoids 18

  17. Non-Holonomic Constraints § Non-holonomic constraints limit the possible incremental movements within the configuration space of the robot. § Robots with differential drive or synchro- drive move on a circular trajectory and cannot move sideways. § XR-4000 or Mecanum-wheeled robots can move sideways (they have no non- holonomic constraints). 19

  18. Holonomic vs. Non-Holonomic § Non-holonomic constraints reduce the control space with respect to the current configuration § E.g., moving sideways is impossible. § Holonomic constraints reduce the configuration space. § E.g., a car and a trailer (not all angles between car and trailer are possible) 20

  19. Drives with Non-Holonomic Constraints § Synchro-drive § Differential drive § Ackerman drive 21

  20. Drives without Non-Holonomic Constraints § XR4000 drive § Mechanum wheels 22

  21. Dead Reckoning and Odometry § Estimating the motion based on the issues controls/wheel encoder readings § Integrated over time 23

  22. Summary § Introduced different types of drives for wheeled robots § Math to describe the motion of the basic drives given the speed of the wheels § Non-Holonomic Constraints § Odometry and Dead Reckoning 24

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