1 CMPUT 412 Motion Control – Wheeled robots Csaba Szepesvári University of Alberta TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AA A A A A AA

2 Motion Control (wheeled robots)  Requirements Kinematic/dynamic model of the robot Model of the interaction between the wheel and the ground Definition of required motion   speed control,  position control Control law that satisfies the requirements

3 Mobile Robot Kinematics  Kinematics Actuator motion  effector motion What happens to the pose when I change the velocity of wheels/joints? Neglects mass, does not consider forces (  dynamics)  Aim Description of mechanical behavior for design and control Mobile robots vs. manipulators  Manipulators: 9 f: £ ! X, x = f( µ )  Mobile robots: (#1 challenge!)  Physics: Wheel motion/constraints  robot motion

4 Kinematics Model  Goal: robot speed  Wheel speeds  Steering angles and speeds  Geometric parameters  forward kinematics  Inverse kinematics  Why not?

5 Initial frame: Robot frame: Robot position: Mapping between the two frames Example: Robot aligned with Y I Representing Robot Positions

6 Example

7 Differential Drive Robot: Kinematics  wheel’s spinning speed  translation of P  Spinning speed  rotation around P wheel 1 wheel 2

8 Differential Drive Robot: Kinematics II.

9 Wheel Kinematic Constraints: Assumptions  Movement on a horizontal plane  Point contact of the wheels  Wheels not deformable  Pure rolling v = 0 at contact point  No slipping, skidding or sliding  No friction for rotation around contact point  Steering axes orthogonal to the surface  Wheels connected by rigid frame (chassis)

10 Wheel Kinematic Constraints: Fixed Standard Wheel

11 Example  Suppose that the wheel A is in position such that   = 0 and  = 0  This would place the contact point of the wheel on X I with the plane of the wheel oriented parallel to Y I. If  = 0, then this sliding constraint reduces to:

12 Wheel Kinematic Constraints: Steered Standard Wheel

13 Wheel Kinematic Constraints: Castor Wheel

14 Wheel Kinematic Constraints: Swedish Wheel

15 Wheel Kinematic Constraints: Spherical Wheel

16 Robot Kinematic Constraints  Given a robot with M wheels each wheel imposes zero or more constraints on the robot motion only fixed and steerable standard wheels impose constraints  What is the maneuverability of a robot considering a combination of different wheels?  Suppose we have a total of N=N f + N s standard wheels We can develop the equations for the constraints in matrix forms: Rolling Lateral movement

17 Example: Differential Drive Robot  J 1 ( ¯ s )=J 1f C 1 ( ¯ s )=C 1f  ® = ? ¯ = ? Right weel: ® = - ¼ /2, ¯ = ¼ Left wheel: ® = ¼ /2, ¯ = 0

18 Mobile Robot Maneuverability  Maneuverability = mobility available based on the sliding constraints + additional freedom contributed by the steering  How many wheels? 3 wheels  static stability 3+ wheels  synchronization  Degree of maneuverability Degree of mobility Degree of steerability Robots maneuverability

19 Degree of Mobility  To avoid any lateral slip the motion vector has to satisfy the following constraints:  Mathematically: must belong to the null space of the matrix Geometrically this can be shown by the Instantaneous Center of Rotation (ICR)

20 Instantaneous Center of Rotation  Ackermann SteeringBicycle

21 Degree of Mobility++  Robot chassis kinematics is a function of the set of independent constraints the greater the rank of, the more constrained is the mobility  Mathematically  no standard wheels  all direction constrained  Examples: Unicycle: One single fixed standard wheel Differential drive: Two fixed standard wheels  wheels on same axle  wheels on different axle

22 Degree of Steerability  Indirect degree of motion The particular orientation at any instant imposes a kinematic constraint However, the ability to change that orientation can lead additional degree of maneuverability  Range of :  Examples: one steered wheel: Tricycle two steered wheels: No fixed standard wheel car (Ackermann steering): N f = 2, N s =2  common axle

23 Robot Maneuverability  Degree of Maneuverability Two robots with same are not necessary equal Example: Differential drive and Tricycle (next slide) For any robot with the ICR is always constrained to lie on a line For any robot with the ICR is not constrained an can be set to any point on the plane  The Synchro Drive example:

24 Wheel Configurations: ± M =2  Differential DriveTricycle

25 Basic Types of 3 -Wheel Configs

26 Synchro Drive

27 Workspace: Degrees of Freedom  What is the degree of vehicle’s freedom in its environment? Car example  Workspace how the vehicle is able to move between different configuration in its workspace?  The robot’s independently achievable velocities = differentiable degrees of freedom (DDOF) = Bicycle: DDOF=1; DOF=3 Omni Drive: DDOF=3; DOF=3  Maneuverability · DOF!

28 Mobile Robot Workspace: Degrees of Freedom, Holonomy  DOF degrees of freedom: Robots ability to achieve various poses  DDOF differentiable degrees of freedom: Robots ability to achieve various path  Holonomic Robots A holonomic kinematic constraint can be expressed a an explicit function of position variables only A non-holonomic constraint requires a different relationship, such as the derivative of a position variable Fixed and steered standard wheels impose non- holonomic constraints

29 Non-Holonomic Systems  Non-holonomic systems traveled distance of each wheel is not sufficient to calculate the final position of the robot one has also to know how this movement was executed as a function of time! differential equations are not integrable to the final position s 1 =s 2 ; s 1R =s 2R ; s 1L =s 2L but: x 1 = x 2 ; y 1 = y 2

30 Path / Trajectory Considerations: Omnidirectional Drive

31 Path / Trajectory Considerations: Two-Steer

32 Beyond Basic Kinematics  Speed, force & mass  dynamics  Important when: High speed High/varying mass Limited torque  Friction, slip, skid,..  How to actuate: “motorization”  How to get to some goal pose: “controllability”

33 Motion Control (kinematic control)  Objective: follow a trajectory position and/or velocity profiles as function of time.  Motion control is not straightforward: mobile robots are non-holonomic systems!  Most controllers are not considering the dynamics of the system

34 Motion Control: Open Loop Control  Trajectory (path) divided in motion segments of clearly defined shape: straight lines and segments of a circle.  Control problem: pre-compute a smooth trajectory based on line and circle segments  Disadvantages: It is not at all an easy task to pre-compute a feasible trajectory limitations and constraints of the robots velocities and accelerations does not adapt or correct the trajectory if dynamical changes of the environment occur The resulting trajectories are usually not smooth

35 Feedback Control  Find a control matrix K, if exists with k ij =k(t,e)  such that the control of v(t) and (t)  drives the error e to zero.

36 Kinematic Position Control: Differential Drive Robot  Kinematics:  : angle between the x R axis of the robots reference frame and the vector connecting the center of the axle of the wheels with the final position yy

37 Coordinate Transformation Coordinate transformation into polar coordinates with origin at goal position: System description, in the new polar coordinates yy for

38 Remarks  The coordinates transformation is not defined at x = y = 0; as in such a point the determinant of the Jacobian matrix of the transformation is not defined, i.e. it is unbounded  For the forward direction of the robot points toward the goal, for it is the backward direction.  By properly defining the forward direction of the robot at its initial configuration, it is always possible to have at t=0. However this does not mean that  remains in I 1 for all time t. a

39 The Control Law  It can be shown, that with the feedback controlled system  will drive the robot to  The control signal v has always constant sign, the direction of movement is kept positive or negative during movement parking maneuver is performed always in the most natural way and without ever inverting its motion.

40 Kinematic Position Control: Resulting Path

41 Kinematic Position Control: Stability Issue  It can further be shown, that the closed loop control system is locally exponentially stable if  Proof: for small xcosx = 1, sinx = x and the characteristic polynomial of the matrix A of all roots have negative real parts.

42 Summary  Kinematics: actuator motion  effector motion Mobil robots: Relating speeds Manipulators: Relating poses  Wheel constraints Rolling constraints Sliding constraints  Maneuverability (DOF) = mobility (=DDOF) + steerability  Zero motion line, instantaneous center of rotation (ICR)  Holonomic vs. non-holonomic  Path, trajectory  Feedforward vs. feedback control  Kinematic control