This document summarizes the key aspects of software architecture for wheeled mobile robots. It discusses common architectures including those without an OS, with a real-time OS, and with an embedded OS. It also covers important components like motion control using PID regulators, localization using odometry and lidar, and motion planning algorithms like A* and RRT Connect. The document provides advantages and disadvantages of the different approaches.

1. Software architecture of
wheeled mobile robots
Dmitry Suvorov

2. Index
1. Introduction
2. General software architecture
3. Motion control
4. Localization and mapping
5. Motion planning

3. Introduction

4. Differential drive

5. Applications
Cleaners
Lawnmowers
Research project
Retail robots
Robots-toys

6. Advantages of differential drive
• Simple controlling algorithms;
• Good mathematical models of the drive;
• Low cost;
• Easy prototyping;
• No slippage.

7. Disadvantages of differential drive
• Low permeability of the robot;
• Low mobility.

8. General software
architecture

9. Types of software architectures
• Simple embedded architectures without OS
• Architecture based on real-time OS (RTOS)
• Architecture based on embedded OS

10. Simple embedded architectures without OS
Advantages:
• Low cost hardware is required
• Easy development
Disadvantages:
• There is no abstraction from hardware.
• It is impossible to create to create advanced systems for performing
difficult tasks.
• Problems with debugging and writing unit tests.
Applications:
• Toys, research projects.

11. Architecture based on real-time OS (RTOS)
Advantages:
• One processor for high level tasks and hardware control.
• Abstraction from hardware level.
Disadvantages:
• Difficult tasks scheduling.
• Difficult logic (high and low tasks are mixed)
Applications:
• Service robots, military projects and research.

12. Architecture based on embedded OS
Advantages:
• Abstraction from hardware level.
• Strong decomposition of tasks on hardware level.
• No scheduling problems.
• Easy decomposition of tasks between software and hardware
developers.
Disadvantages:
• Higher cost.
Applications:
• Service robots, toys, military projects
and research.

13. Typical architecture of the controlling system
Decision making
Motion planning Motion control Localization
SLAM
(optionally)

14. Motion control

15. Tasks
• Rotating in place
• Following lines
• Following arbitrary trajectory

16. Automatic control theory
Advantages:
• Simple well-known theory.
• Easy to implement on hardware and software levels.
• Can work on slow processors.
• There are heuristic methods for tuning parameters.
Disadvantages:
• It is practically impossible to archive high precision of motion.
• It is difficult to calculate parameters of controlling algorithms.

17. PID regulator
Discrete form:
u(t) = P(t) + I(t) + D(t)
P(t) = Cp * e(t)
I(t) = I(t – T) + Ci * e(t)
D(t) = Cd * ( e(t) – e(t-T) )
Cp, Ci, Cd – coefficients of PID
regulator;
T – period (time between calls of
regulator).

18. Tuning parameters of PID regulator
• P – current error compensation
• I – statical error compensation
• D - oscillations damping
Ziegler–Nichols method:
K – coefficient of P-regulator when system become unstable.
T – period of oscillations
P = 0.6 * K
I = 2 * P / T
D = P * T / 8

19. Robot motion control
PID regulator for controlling rotation
PD regulator for controlling moving

20. Open source implementations
www.ros.org
www.mrpt.org

21. Localization and mapping

22. Task
To control the robot we need to know its real position.
Problems:
• There is no universal sensor for getting accurate absolute robot
position.

23. Odometry
We can get data from encoders and calculate relative robot position

24. Numerical form of odometry

25. Odometry
Advantages:
• No need in additional sensors.
Disadvantages:
• Low accuracy.
• Error increases with time.
• High sensitivity to slippage.

26. Lidar based localization
Advantages:
• High accuracy.
• Error does not increase with time.
• Can be implemented on slow processors.
Disadvantages:
• Map of the environment is required.

27. Methods of localization
• Particle filter based.
• Kalman filter based.

28. Particle filter based localization

29. Open source implementations
www.ros.org
www.mrpt.org
openslam.org

30. Motion planning

31. Task
• We need to find path to destination on the map before start of
movement.
Methods:
• Optimal (A*, Dijkstra search …)
• Suboptimal (RRT Connect…)

32. A*
Advantages:
• It always finds the shortest way.
Disadvantages:
• High performance processor is required.

33. RRT Connect
Advantages:
• Very fast.
• Can search trajectories in high
dimension spaces.
Disadvantages:
• The found path is not optimal.

34. Contacts
Dmitry Suvorov
d.suvorov90@gmail.com
Skoltech Space Robotics Laboratory
wicron.com lexybot.com