Vision system implementation on Bioloid robot

Tato bakalářská práce se zabývá implementací systému vidění na dvounohý humanoid robot ze stavebnice Bioloid. Systém vidění je složen z bezdrátové kamery, která je namontovaná na robotovi a z řídícího počítače. Cílem této práce bylo zkonstruovat a oživit humanoidního robota, vytvořit systém vidění a bezdrátový komunikační systém. V centru je robot, který pomocí bezdrátové komunikace současně odesílá i přijímá údaje. Tento systém nabízí skvělé schopnosti na další rozšíření.This bachelor's thesis deals with vision system implementation on bipedal humanoid robot made of the Bioloid assembly kit. The vision system is composed of a wireless camera, mounted on the robot and the controlling computer. The goal of this work was to construct and vitalize the humanoid robot, to establish the vision system and to create a wireless communication system. The center of this system is the robot, which wirelessly sends and receives data simultaneously. This system offers great capabilities for further expansions.

Using robot operating system (ROS) and single board computer to control bioloid robot motion

This paper presents a research study on the adaptation of a novel technique for placing a programmable component over the structural component of a Robotis Bioloid humanoid robot. Assimilating intelligence plays an important role in the field of robotics that enables a computer to model or replicate some of the intelligent behaviors of human beings but with minimal human intervention. As a part of this effort, this paper revises the Bioloid robot structure so as to be able to control the robotic movement via a single board computer Beaglebone Black (BBB) and Robot operating system (ROS). ROS as the development frame work in conjunction with the main BBB controller that integrates robotic functions is an important aspect of this research, and is a first of its kind approach. A full ROS computation has been developed by which an API that will be usable by high level software using ROS services has also been developed. The human like body structure of the Bioloid robot and BeagleBone Black running ROS along with the intellectual components are used to make the robot walk efficiently

Using robot operating system (ROS) and single board computer to control bioloid robot motion

This paper presents a research study on the adaptation of a novel technique for placing a programmable component over the structural component of a Robotis Bioloid humanoid robot. Assimilating intelligence plays an important role in the field of robotics that enables a computer to model or replicate some of the intelligent behaviors of human beings but with minimal human intervention. As a part of this effort, this paper revises the Bioloid robot structure so as to be able to control the robotic movement via a single board computer Beaglebone Black (BBB) and Robot operating system (ROS). ROS as the development frame work in conjunction with the main BBB controller that integrates robotic functions is an important aspect of this research, and is a first of its kind approach. A full ROS computation has been developed by which an API that will be usable by high level software using ROS services has also been developed. The human like body structure of the Bioloid robot and BeagleBone Black running ROS along with the intellectual components are used to make the robot walk efficiently

Optimization of Humanoid Robot Leg Movement Using Open CM 9.04

The Indonesian Robot Dance Contest (KRSTI) is a branch of the Indonesian Robot Contest (KRI) with the theme of dance. The robot used is a humanoid robot that can dance. Every year at the event, the provisions for robots constantly change, both the type of dance being demonstrated and the requirements for the robot's height. The taller the robot, the more difficult it is to control its walking movements because of the load it carries. This study uses a suitable algorithm to make the walking movement more natural and minimize the robot's falling. Human ROM data is used as a parameter for the range of motion of the servos that act as joints in the robot's legs. The algorithm created serves to determine the initial position of the angle on the servo to avoid the wrong initial movement position between one servo and another. The robot used is the Bioloid Robot’s leg Type A and uses OpenCM 9.04-A as the controller. The results showed that ROM on human feet could not be fully implemented on robot legs due to the robot's structure and the need for a robot that only relies on an algorithm to find the correct fulcrum to maintain balance. The comparison results show that the movement when walking on the ankle (ID servo 15) ranges from 749-567, while the ROM range is only between 580-512. When walking (servo ID 16), movement ranges from 460-291, while the ROM range ranges from 580-512

A Robot Operating System (ROS) based humanoid robot control

This thesis presents adapting techniques required to enhance the capability of a commercially available robot, namely, Robotis Bioloid Premium Humanoid Robot (BPHR). BeagleBone Black (BBB), the decision-making and implementing (intelligence providing) component, with multifunctional capabilities is used in this research. Robot operating System (ROS) and its libraries, as well as Python Script and its libraries have been developed and incorporated into the BBB. This fortified BBB intelligence providing component is then transplanted into the structure of the Robotis Bioloid humanoid robot, after removing the latter’s original decision-making and implementing component (controller). Thus, this study revitalizes the Bioloid humanoid robot by converting it into a humanoid robot with multiple features that can be inherited using ROS. This is a first of its kind approach wherein ROS is used as the development framework in conjunction with the main BBB controller and the software impregnated with Python libraries is used to integrate robotic functions. A full ROS computation is developed and a high level Application Programming Interface (API) usable by software utilizing ROS services is also developed. In this revised two-legged-humanoid robot, USB2Dynamixel connector is used to operate the Dynamixel AX-12A actuators through the Wi-Fi interface of the fortified BBB. An accelerometer sensor supports balancing of the robot, and updates data to the BBB periodically. An Infrared (IR) sensor is used to detect obstacles. This dynamic model is used to actuate the motors mounted on the robot leg thereby resulting in a swing-stance period of the legs for a stable forward movement of the robot. The maximum walking speed of the robot is 0.5 feet/second, beyond this limit the robot becomes unstable. The angle at which the robot leans is governed by the feedback from the accelerometer sensor, which is 20 degrees. If the robot tilts beyond a specific degree, then it would come back to its standstill position and stop further movement. When the robot moves forward, the IR sensors sense obstacles in front of the robot. If an obstacle is detected within 35 cm, then the robot stops moving further. Implementation of ROS on top of the BBB (by replacing CM530 controller with the BBB) and using feedback controls from the accelerometer and IR sensor to control the two-legged robotic movement are the novelties of this work

A teleoperation system to control the humanoid robot using an RGB-D sensor

This paper presents a concept design of the work algorithm for a teleoperation control system of a humanoid robot. The humanoid robot control system needs to stabilize the robot in a vertical position in order to prevent the robot from falling. The process of design of the control system includes the design of position filter to detect the unstable positions. The application of such a control system enables to control the humanoid robot using motion capture technology

Separating Multi Speeches in Intelligent Humanoid Robot using FastICA

The main objective of our research is to develop an intelligent humanoid robot for teaching children by listening and answering the questions. In our previous research, we have designed a humanoid robot that can detect human face and receive commands by using speech recognition. Our robot is based on Bioloid GP robot and Raspberry Pi2 as control system. In this study, we would like to expand the capability of the robot system in order to isolate the speech of one speaker from all the other sounds. The problem for separating multi speeches from stereo audio record is called as Blind Speech Separation (BSS). We propose FastICA algorithm to solve the BSS problem. FastICA is an efficient algorithm to separate several signals based on Independent Component Analysis (ICA) algorithm. Some assumption must be met to use FastICA, that is the number of mixtures are equal to the number of sources and the sources are linearly independent from each other. To evaluate the algorithm, we use several simulations based on two speech sources and its mixing matrix. Our simulation shows FastICA algorithm can solve BSS problem by separating two sound signals, but its linearly independent assumption makes it difficult to implement in our humanoid robo

A teleoperation system to control the humanoid robot using an RGB-D sensor

This paper presents a concept design of the work algorithm for a teleoperation control system of a humanoid robot. The humanoid robot control system needs to stabilize the robot in a vertical position in order to prevent the robot from falling. The process of design of the control system includes the design of position filter to detect the unstable positions. The application of such a control system enables to control the humanoid robot using motion capture technology