Embedded Motion Control 2017 Group 9: Difference between revisions

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== evaluation ==
== evaluation ==
The first trial used our old program that has proven itself as seen in the video below. Unfortunately we did not upload the correct version. <br>
The first trial used our old program that has proven itself as seen in the video below. Unfortunately we did not push the correct version to PICO. <br>
 
The second trial used our latest program. The potential field is added because there exists a chance that PICO would run into the walls without it. <br>
The second trial used our latest program. The potential field is added because there exists a chance that PICO would run into the walls without it. <br>
The new program works in the simulation, it has been tested in the real setting and we had problems with the odometer to correctly make the turning. <br>
The debugging of the program had to do without the testing in the real setting.


= Maze challenge =
= Maze challenge =

Revision as of 20:47, 8 June 2017

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

The initial design for the maze challenge is elaborated below. It includes the requirements, functions, components, schematic of program structure, specifications and interfaces to define the working of PICO. The file for the initial design is included here: File:Assignment-for-week1.pdf

Requirements

➢ PICO drives autonomously through maze
➢ Being able to take a turn without touching a wall
➢ Being able to detect a turn or branching corridors
➢ Avoiding collisions with obstacles (including the walls)
➢ Driving straight and rotating smoothly
➢ PICO should not stand still for 30 seconds
➢ Avoid getting trapped in a loop of the maze
➢ Being able to recognize the door

Functions

Functionsg9.jpeg

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

- maximum translational speed of 0.5 m/s
‐ maximum rotational speed of 1.2 rad/s
‐ Door template: length of 0.5 ‐ 1.5m and with side walls of approximately 30cm, see figure below
‐ LRF accuracy and range unknown
‐ odometer accuracy unknown

Doortempg9.jpeg

Interfaces

The odometer and LRF generates data for mapping the environment.

The algorithm sets nodes on the junction as a setpoint for navigation, plans the route and put the actuators to work accordingly.

The odometer and LRF keeps on keeping track of the environment and the software recognizes obstructions, dead ends that might be doors and junction.

Corridor challenge

design

At first, PICO moves forward with a modified potential field.
When it detects the junction, the potential field goes off and stops when it is in the middle of the junction.
PICO then rotates 90 degree and moves forward.
When PICO detects that it is inside the junction, the potential field goes on and finishes the challenge.

result

The corridor challenge failed

In the first trial PICO moved straight forward without potential field.
When it detects the junction it stopped and rotated 90 degrees in the wrong direction.
This inevitably resulted into crashing into the walls.

The second trial PICO did not detect the junction and drove straight forward, this is the latest program we had.

evaluation

The first trial used our old program that has proven itself as seen in the video below. Unfortunately we did not push the correct version to PICO.

The second trial used our latest program. The potential field is added because there exists a chance that PICO would run into the walls without it.
The new program works in the simulation, it has been tested in the real setting and we had problems with the odometer to correctly make the turning.
The debugging of the program had to do without the testing in the real setting.

Maze challenge

design

result

evaluation