Embedded Motion Control 2018 Group 6

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Group members

Name: Report name: Student id:
Thomas Bosman T.O.S.J. Bosman 1280554
Raaf Bartelds R. Bartelds add number
Bas Scheepens S.J.M.C. Scheepens 0778266
Josja Geijsberts J. Geijsberts 0896965
Rokesh Gajapathy R. Gajapathy 1036818
Tim Albu T. Albu 19992109
Marzieh Farahani Marzieh Farahani Tutor


Initial Design

Requirements and Specifications

Use cases for Escape Room

1. Wall and Door Detection

2. Move with a certain profile

3. Navigate


Requirements for Escape Room

R1.1 The system shall detect walls without touching them

R1.2 The system shall detect the goal/door

R1.3 The system shall log and map the environment


R2.1 The system shall move slower than 0.5 m/s translational and 1.2 rad/s rotational

R2.2 The system shall not stay still for more than 30 seconds


R3.1 The system shall find the goal

R3.2 The system shall determine a path to the goal

R3.3 THe system shall navigate to the goal

R3.4 THe system shall not touch the walls

R3.5 The system shall complete the task within 5 minutes

Use cases for Hospital Room

(unfinished)

1. Mapping

2. Move with a certain profile

3. Orient itself

4. Navigate

Functions, Components and Interfaces

The program which will be running on the Pico can be categorized in four different components: perception, monitoring, plan and control. They exchange information through the world model, which stores all the data. Below, the functions of the four components are described.


Perception: ERC: input: lrf-data process (filter) the laser-readings result for world model: distances to objects

HC: input: lrf-data, odometry process both sensors with gmapping process (filter) the laser-readings result for world model: map, distances+angles to objects


Monitoring: ERC: input: distances to objects process distances to determine situation: following wall, (near-)collision, entering corridor, escaped room result for world model: state of situation

HC: input: map, distances to objects process distances and map to determine situation: following path, (near-)collision, found object result for world model: state of situation


Plan: ERC: input: state of situation determine next step: prevent collision, continue following wall, stop because finished result for world model: state of next step

HC: input: state of situation determine next step: goto new waypoint, continue following path, prevent collision, go back to start, stop because finished determine path to follow result for world model: state of next step


Control: ERC: input: distances+angles to objects, state of next step determine setpoint angle and velocity of robot result for world model: setpoint angle and velocity of robot

HC: input: state of next step, path to follow determine setpoint angle and velocity of robot result for world model: setpoint angle and velocity of robot

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