Mobile Robots Locomotion & Sensors

Transcription

1 Mobile Robots Locomotion & Sensors Institute for Software Technology 1

2 Robotics is Easy control behavior perception modelling domain model environment model information extraction raw data planning task cognition reasoning path planning navigation path execution actuator commands sensing acting environment/world 2

3 Locomotion we want mobile robots mainly wheeled Sensors why do we need sensors? sensors for motion sensors for the environment Today s Agenda 3

4 Challenges for Intelligent Autonomous Robots Computer Vision Planning and Decision Making Human-Robot Interaction 3D Object Recognition Sensors Localization Mapping Knowledge Representation Machine Learning Knowledge Acquisition Reasoning and Interpretation Dependability Path Planning and Navigation Grasping and Manipulation Actuators many more 4

5 Literature Introduction to Autonomous Mobile Robots. 2 nd Edition. Roland Siegwart, Illah Reza Nourbakhsh, Davide Scaramuzza. MIT Press Springer Handbook of Robotics. Bruno Siciliano and Oussama Khatib. Springer

6 Locomotion Oxford Dictionary: movement or the ability to move from one place to another 6

7 Locomotion a mobile robot needs locomotion has a long history in nature different optimizations for speed stability efficiency 7

8 Locomotion in Biological Systems [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] 8

9 biological locomotion is hard to replicate mechanical complexity duplication miniaturization actuation energy storage Inspiration by Nature [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] 9

10 Wheel Types standard castor Swedish spherical Side View Front View Top View [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] 10

11 Typical Arrangements (2 and 3 Wheels) 2 Wheels 3 Wheels [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] 11

12 Typical Arrangements ( 4 Wheels) [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press]

13 NASA Mars Rover - Rocker-Bogie hybrid between walking and driving allows to climb obstacles reduce movement of body Advanced Mechanisms [Nasa/JPL] 13

14 Homogeneous Transformation we need a transformation between the motion in the reference frame I and the robot frame R the transformation depend on the global angle θ ξ I = [X I, Y I, θ] T ξ I = IR R (θ) ξ R = I R R (θ) [X R, YR, θ ] T I R R (θ) = cos θ sin θ 0 sin θ cos θ

15 Kinematic Constraints an arrangement comprises n wheels of different types each wheel i provides an individual velocity φ i and individual parameters, e.g. steering angle to determine the maneuverability of a configuration we use 2 sorts of constraints rolling constraints: all motions in the wheel plane have to be accompanied with the appropriate wheel spin sliding constraints: the motion orthogonal to a (standard) wheel has to be zero 15

16 Fixed Standard Wheel ξ R = [X R, YR, θ ] T sin α + β cos α + β l cos β R θ ξ I rφ = 0 RKC [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] cos α + β sin α + β l sin β R θ ξ I = 0 SKC 16

17 Steered Standard Wheel same as fixed standard wheel expect steering is now a function of time β(t) ξ R = [X R, YR, θ ] T [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] sin α + β t cos α + β t l cos β(t) R θ ξ I rφ = 0 RKC cos α + β(t) sin α + β(t) l sin β(t) R θ ξ I = 0 SKC 17

18 Swedish Wheel [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] sin α + β + γ cos α + β + γ l cos(β + γ) R θ ξ I rφ cos γ = 0 RKC cos α + β + γ sin α + β + γ l sin(β + γ) R θ ξ I rφ sin γ r sw φ sw = 0 SKC 18

19 Spherical Wheel same as fixed standard wheel expect steering is now a free variable β [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] sin α + β cos α + β l cos β R θ ξ I rφ = 0 RKC cos α + β sin α + β l sin β R θ ξ I = 0 SKC 19

20 Combining the Constraints I the wheel arrangement comprises N f fixed and N s steerable wheels, N = N f + N s β s (t) denotes the steering angles while β f denotes all fixed angles φ f t denotes wheel speed of the fixed wheels while φ s t denotes wheel speed of the steered wheels, φ t = φ f t denotes the combination φ s t 20

21 Combining the Constraints II Rolling Constraints J 1 β s R θ ξi J 2 φ = 0 with J 1 β s = J 2 = Sliding Constraints r r N C 1 β s R θ ξi = 0 with C 1 β s = All Together J 1 β s C 1 β s R θ ξ I = J 2φ 0 C 1f C 1s (β s ) J 1f J 1s (β s ) and 21

22 Maneuverability we can use the constraints to investigate the mobility potential of a robot the degree of mobility is defined as: δ m = 3 rank C 1 β s represents the number of DOF that can immediately manipulated by changes in the wheel velocities related to the location of the instantaneous center of rotation (ICR) the degree of steerability is defined as: δ s = rank C 1s β s 0 δ s 2 depends on the number of steerable wheels robot maneuverability δ M = δ m + δ s related to the DOF a robot is able to manipulate 22

23 Why do we talk about Sensors? why should we care about sensors? key component of a robot for perceiving the environment sensor information allows modeling understanding sensors enable appropriate use why should we understand sensors and their underlying principles to properly select sensors for a given application to properly model the sensor, e.g. resolution, bandwidth, errors 23

24 Turtlebot2 inexpensive robot platform for research and teaching based on the open version of the irobot Roomba (Create) provides a lot of sensors wheel encoder/odometry gyroscope bumpers cliff sensors wheel drop sensor infrared sensor for docking station Microsoft Kinect [Robotnik] 24

25 Properties of Sensors sensors for robots are different in 3 basic dimensions functional perspective proprioceptive sensors: measure internal values of the robot, e.g. speed of the robot exteroceptive sensors: measure the environment of the robot, e.g. camera operation mode passive sensors: measures the ambient environmental energy, e.g. temperature sensor active sensors: emits energy into the environment and measures the environment's response, e.g. laser rage finder reference frame local/incremental: reports only a delta, e.g. gyroscopes global/absolute: reports an absolute value, e.g. GPS 25

26 Errors of Sensors sensors are never 100% precise accuracy: defines the conformity between the reported value m and the true value v, accuracy = 1 m v v systematic errors: caused by factors and processes that can be modelled in theory, they are predictable and deterministic random errors: cannot be predicted, modelled with probabilistic methods precision: describes the reproducibility of measurements, precision = range σ 26

27 Types of Sensors sensors interesting for mobile robots can be roughly divided in two types motion and position sensors related to the position of the robot and its change environment sensors related to the perception of the environment of the robot 27

28 MOTION & POSITON SENSORS 28

29 Wheel Encoder measure the angular position of a wheel (or shaft) in general a relative sensor realized as opto-mechanic device optic readout of an encoder disk 2 encoder signals to detect direction of movement [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] 29

30 Inertial Measurement Unit (IMU) device to estimate of the movement of a vehicle with respect to an inertial frame relative position (x, y, z) orientation (roll, pitch, yaw), velocity acceleration needs at least 3 gyroscopes 3 accelerometer can be combined with compass global positioning system (GPS) Xsems IMU mti-10 (image Xsens) 30

31 IMU Systems [Sicillano, Khatib, 2008, Springer] IMUs are extremely sensitive devices errors in the gyroscopes and accelerometers drift of the gyroscopes compensation of the gravity vector in the accelerometers acceleration is integrated twice, quadratic error in position on the long run an absolute correction is necessary, e.g. GPS 31

32 Gyroscope gyroscopes measure the change of orientation of a system uses a fast spinning rotor principle of conservation of the angular momentum, L = Iω stable axis heading sensor drift due to mechanical drawbacks, e.g. friction good quality possible, 0.1 in 6h (~ $) used in aircraft, missiles, and submarines [Sicillano, Khatib, 2008, Springer] 32

33 Optical Gyroscopes gyroscope based on the Sagnac effect two monochromatic light beams from the same source travels along the same path one travels CW, the other CCW if the path rotates, on beam encounters a slightly shorter path difference can be measured trough phase shift realization with optical fiber, ~ 5km Δt = 2πR 1 1 c ω R c + ω R ω R [D. McFadden, Wikipedia] 33

34 Accelerometer accelerometer measures all external forces applied to them including gravity realized as spring-mass-damper system F applied = F inertial + F damping + F spring = mx + cx + kx [Sicillano, Khatib, 2008, Springer] at steady-state a applied = kx m 34

35 Realization as MEMS accelerometer, gyroscopes and IMUS can be manufactured nowadays compactly and cheaply micro-electro-mechanical systems (MEMS) allow compact manufacturing mass commercialization allow high volumes and low prices, e.g. smart phones or gaming industry (Nintendo Wee) springs mass variable capacitor 35

36 Beacons elegant way to measure the position of a mobile robot beacon is a signal plus a location used since centuries natural vs. artificial active vs. passive examples are landmarks, light houses, radio transmitter, GPS, indoor localization non-directional beacons triangulation for position estimation [Alvesgaspar, Wikipedia] 36

37 ENVIRONMENT SENSORS 37

38 Tactile Sensors measure contact with an object measure trough physical interaction have to be robust, repetitive interaction simple bumper sensors for obstacle avoidance simple (binary) switch complex tactile skin enhanced spatial resolution enhanced force resolution for complex interaction with environment/humans [icub Project, Wikipedia] 38

39 Ultrasonic Sensors measures distances using ultrasound frequency > 20kHz, typically ~40kHz principle time of flight measure the time t between a signal emission and reception of an echo distance to object d = c t 2 wave velocity: c sound 0.3 km s, c light 0.3 km μs comprises a microphone a speaker (sometimes combined) [Devantec SF04] [Sicillano, Khatib, 2008, Springer] 39

40 Ultrasonic Sensors - Properties ultrasound sensors are cheap but have some drawbacks limited spatial resolution wide sensor cone wrong & slow measurement frequency low sound speed jitter environment changes wrong distance smooth surfaces [Sicillano, Khatib, 2008, Springer] 40

41 Phase Shift Measurement measures distance using the phase shift of signals emitting amplitude-modulated light with a know frequency f diffuse reflection at an object with roughness larger than the light s wavelength λ measure the phase shift of the original and reflected signals ambiguity if modulated wavelenght λ is similar to distance D = 1 θ 2 2π λ = 1 θ c 2 2π f [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] 41

42 2D Laser Range Finder (LRF) popular sensor for robotics used for numerous task localization mapping object recognition principle phase shift measurement a number of coaxial laser beams advantages high precision and reliability wide field of view good maximum range, up to several 100 m good spatial resolution, decreases with distance Hokuyo UTM-30LX [Hykuyo Inc.] Sick LMS 100 [Sick AG] 42

43 2D LRF - Principle function typical data set polar coordinates array [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] 43

44 3D Laser Range Finder acquire a 3D point cloud of the environment two basic principles rotate or tilting a 2D laser range finder cheap but slow special device with several simultaneous laser beams rotating Sick LMS 200 price ~ 4000 LMS: Hz ~27k values/s FOV: 360 x ~ 180 [Velodyne] [University Osnabrück] Velodyne HDL-64E price ~ laser beams 15Hz vertical spinning ~ 1.3M values/s 44

45 3D Laser Scan 3D laser scan Loiblpass Tunnel 45

46 time-of-flight camera Mesa SwissRanger uses a similar principle as laser range finder principle illuminates the scene at once measures for each pixel the time between emission and detection triangulation for distance advantage all pixels are measured in parallel reduces motion blur drawback needs measurement of ultra short time limited resolution 176 x 144 pixels Mesa SwissRanger 4000 [Mesa Imaging] 46

47 Structured Light one drawback of stereo cameras is finding the correspondence in particular with limited texture better solution emitting structured light, e.g. known stripes or patterns light perceived by the camera range of illuminated point determined with simple geometry [Siegwart, Nourbakhsh, Scaramuzza, 2011, MIT Press] 47

48 Microsoft Kinect popular 3D range sensor cheap trough mass commercialization, Microsoft XBox use the principle of structured light comprises infrared laser projector infrared camera RGB camera microphone array motorized tilt unit [Siegwart, Scaramuzza] 48

49 Microsoft Kinect Infrared Pattern [Siegwart, Scaramuzza] 49

50 Microsoft Kinect Depth Image [Siegwart, Scaramuzza] 50

51 Questions? Thank you! 51