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Robots | oGnaCgnouC

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Robots

Scalpel : Mechanical design of an android based mobile robot

Since few month we started to design a wheeled robot base on the android OS. We are a group of robot’s addicted, professional or not, and we share our off time doing robot as an hobby.

3D CAD Model

We found many wheeled robot on the market, but nothing corresponding to our goals. So, we decide to design the one we want. On a previous post, Bilock introduced the Scalpel project. Here is more details about the Scapel’s mechanic design.

Our robot must be :

  • Android based
  • Fast, precise and responsive
  • Fully autonomous
  • Robust and easily assembled

We try to keep the design modular, so you could use this robot locomotion in your own project.

For each topic introduced here, I tried to give a theoretical overview combined with some manufacturing details. I would also try to give you tip and trick to create your own robot based on this scalpel kit. Later, with the scalpel team, we will take a confrontation between the theoretical analysis and experimental results.

Capacities of responsive and accurate displacements

The first step is to determine the mechanical characteristics of the robot’s locomotion. The reactivity of the platform is directly connected to the acceleration and deceleration capabilities without loss of grip. We will see the importance of choosing wisely the coordinates of the center of gravity and the importance of the grip between wheels and the ground.

The electric motors

Then we explain the motor choice to achieve the desired performance. We will detail the operating characteristics of a DC motors and the importance of specific power supplies. Electric motors for our robot, are controlled by PWM command. We will describe the signal command characteristics to optimise the locomotion precision and reactivity while securing the hardware against possible damage.

 

The control systems of rotary sensor wheels

Odometric wheels are use to estimate the position of a moving robot. This system is generally made by wheels connected to rotary encoders. Encoder are generally directly linked to the motor, but this assumes that the wheel is permanently in the contact with the ground and the friction is perfect. Here we explore an original solution of a decoupled odometric wheels. Encoders that are available on the market are expensive and the mechanical integration of this decoupled wheel is not trivial. I would show how, using an Hall effect sensors “1024 increments per revolution” and the minimum number of mechanic parts, that it is possible to manufacture a robust encoder wheel for an affordable cost.

 

Systems of perceptions by IR sensors

Since we want this robot being autonomous, we need to use efficient obstacle detection sensors in order to avoid obstacle collision. As a first step, we integrated the famous Sharp GP2D120. I know that software developers are never happy, they always want to modify the IR sensors angle but the Sharp senors packaging do not allow rapid orientation of the sensors. I will detail the mechanical changes I did on the Sharp infrared sensors packaging to allow my “never satisfied” friends to change quickly the sensor orientation.


Veltrop and his nao “Kinect Controlled Treadmill and Robot Navigation”

Taylor Veltrop did a nice work with his nao robot. I think that he want to be the first to fully teleoperate nao :)


Scalpel robot 1.5 : Android wheeled robot and IOIO board

Scapel 1,5kg proto - Side view

Since few weeks I’m playing with the IOIO Board during my off time. This project is designed to be connected to a Android phone.

The target of this project is to create a high precision 2 wheels robot driven by an Android phone and release as an open source project. I call it the Scalpel. Max speed will be around 2 meter/second and positionning is done by 2 fully independent odometric wheels and distance sensors (sharp gp2d120). Weight will be 1.5kg or 6kg depending of motors and H Bridge power. Due to wheels size this robots will be more appropriate to be used on a flat floor such as a robotic competition floor or sport hall.

I bought the first board on Sparkfun : IOIO 10585. But since, a new version was release : IOIO 10748. This board has been develop by ytai as an open source project. It is a very active project and many information could be find here : ytai blog or here : IOIO google group

general view of IOIO board

(continue reading…)


Nao ! bring me a beer!

Nao : “there is no beer anymore master, do you want a coca cola?”

Help to Orebro University, Nao can now bring a bottle. With the help of his robotics friend : the fridge ;)

Description extracted from the youtube page :

This video demonstrates the integration of the humanoid robotic platform Nao within a Network Robot System (NRS) application. The specific scenario of interest takes place in a smart home environment; the task being that of bringing a can of soda from a fridge to a human user. We use this concrete
scenario to evaluate how the performance of such a robot can be affected by being embedded inside an intelligent domestic environment. This study points out that, by cooperating with different components on the network the overall performance of the robot is increased.


Robot makes ethical decisions ?

Nice to see Nao on a such interesting project. Do not expect to much of the term “ethical decision” ;) but Susan and Michael Anderson think and progress on this wide and complex subject. Article found  on : discovery (thanks to JC)

Irremediably link to this :

(continue reading…)

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