Embedded Motion Control 2017 Group 9

Group Members

Name:	Student id:
Mian Wei	X
Zhihao Wu	X
Petrus Teguh Handoko	X
Bo Deng	X
Bo Cong	X
Jian Wen Kok	X
Nico Huebel	Tutor

Initial Design

File:Assignment-for-week1.pdf

Requirements

➢ PICO drives autonomously through maze
➢ PICO should find the exit and the whole robot is across the finish line within 5 minutes.
➢ PICO is able to deal with approximately axis‐aligned walls, open spaces and loops in the maze.
➢ The task has to be finished within 2 attempts in 7 minutes.
➢ PICO should not stand still for 30 seconds which counts as an attempt
➢ PICO may not touch the wall
➢ The whole PICO should stop within 1.3m to a dead end, and detect whether the dead end is a door.
➢ PICO should detect every dead it meet
➢ At the exit PICO should drive forward for 40 cm
➢ The software is easy to set‐up

Functions

Components

drive control ‐ Holonomic base (omni‐wheels) ‐ Pan‐tilt unit for head detection ‐ 170◦ wide‐angle camer ‐ Laser Range Finder (LRF) ‐ Wheel encoders (odometry) ‐ Asus Xtion Depth sensor world model computer ‐ Intel I7 ‐ Ubuntu 14.04

Specifications

The goal and the requirements will be achieved with the following specifications:

Robot

• The maximum transnational speed of the robot is 0.5 m/s
• The maximum rotational speed equals 1.2 rad/s
• The corridor challenge has to be solved in 5 minutes
• The maze challenge has to be solved in 7 minutes
• Both challenges have a maximum of two trials
• The laser range finder (LRF) has a range of 270 degrees
• The wheel encoders have an unknown accuracy
• The robot must not be idle for more than 30 seconds

Maze

• The corners will be approximately 90 degrees
• The wall distance is 0.5-1.5 meter
• There is only 1 door in the maze
• The door starts opening in 2 seconds
• The door opens if the robot is within 1.3 meter of the door
• The door is open in 5 seconds
• The number of rings must not be larger than the number of potential doors
• The maze may contain loops
• The maze can contain dead ends

Interfaces

The main relations between the interfaces are colored red and can be described as follows:

World model -> Task:The world model can give information about taken paths to the Task
World model -> Skill:The stored observations in the world model are used for movement skills
World model -> Motion:The world model can give data to the actuators
World model -> User interface: The user interface needs the data from the world model to visualize the world model to the human
Task -> World model:The task needs to store information about paths in world model
Skill -> World model :The world model is build from observations
Motion -> World model :The motion can give sensor data about the position to the world model