Low Cost Quadruped: MUTT

The field of educational and research robotics is alight with development platforms that fall short of being interesting and novel. Our goal was to create a quadruped for use as an entry level research project for students and educators. Reducing cost through the use of commercially available parts combined with rapid-prototyping, we built a platform that can be used to teach and learn legged locomotion for less than $600 (half the price of a Turtlebot 2 from OSRF). Our robot was able to walk in basic form using limited actuation; this was limited by the components we chose - specifically the motor controllers for part of the actuation. We expect that using components better suited to the task could accomplish what we set out to achieve

Low Cost Quadruped: MUTT

The field of educational and research robotics is alight with development platforms that fall short of being interesting and novel. Our goal was to create a quadruped for use as an entry level research project for students and educators. Reducing cost through the use of commercially available parts combined with rapid-prototyping, we built a platform that can be used to teach and learn legged locomotion for less than $600 (half the price of a Turtlebot 2 from OSRF). Our robot was able to walk in basic form using limited actuation; this was limited by the components we chose - specifically the motor controllers for part of the actuation. We expect that using components better suited to the task could accomplish what we set out to achieve

PARbot: Personal Assistive Robot

The aging population of the United States is creating a growing need to provide assistive care for elderly and people with disabilities. As the Baby Boomer generation enters retirement, the ratio of caregivers to those that require assistance is projected to decrease. There are currently no commercially available modular assistive robots that can fill this need. Our project aims to provide an alternative to current assisted living options through the development, construction, and testing of a Personal Assistive Robot (PARbot) that allows individuals with general or age related disabilities to maintain some aspects of their independence, such as the ability to shop

Autonomous navigation with ROS for a mobile robot in agricultural fields

Autonomous monitoring of agricultural farms and fields has recently become feasible due to continuing advances in robotics technology, but many notable challenges remain. In this paper, we describe the state of ongoing work to create a fully autonomous ground rover platform for monitoring and intervention tasks on modern farms that is built using inexpensive and off the shelf hardware and Robot Operating System (ROS) software so as to be affordable to farmers. The hardware and software architectures used in this rover are described along with challenges and solutions in odometry and localization, object recognition and mapping, and path planning algorithms under the constraints of the current hardware. Results obtained from laboratory and field testing show both the key challenges to be overcome, and the current successes in applying a low-cost rover platform to the task of autonomously navigating the outdoor farming environment

Intelligent Navigation Service Robot Working in a Flexible and Dynamic Environment

Numerous sensor fusion techniques have been reported in the literature for a number of robotics applications. These techniques involved the use of different sensors in different configurations. However, in the case of food driving, the possibility of the implementation has been overlooked. In restaurants and food delivery spots, enhancing the food transfer to the correct table is neatly required, without running into other robots or diners or toppling over. In this project, a particular algorithm module has been proposed and implemented to enhance the robot driving methodology and maximize robot functionality, accuracy, and the food transfer experience. The emphasis has been on enhancing movement accuracy to reach the targeted table from the start to the end. Four major elements have been designed to complete this project, including mechanical, electrical, electronics, and programming. Since the floor condition greatly affecting the wheels and turning angle selection, the movement accuracy was improved during the project. The robot was successfully able to receive the command from the restaurant and go to deliver the food to the customers\u27 tables, considering any obstacles on the way to avoid. The robot has equipped with two trays to mount the food with well-configured voices to welcome and greet the customer. The performance has been evaluated and undertaken using a routine robot movement tests. As part of this study, the designed service wheeled robot required to be with a high-performance real-time processor. As long as the processor was adequate, the experimental results showed a highly effective search robot methodology. Having concluded from the study that a minimum number of sensors are needed if they are placed appropriately and used effectively on a robot\u27s body, as navigation could be performed by using a small set of sensors. The Arduino Due has been used to provide a real-time operating system. It has provided a very successful data processing and transfer throughout any regular operation. Furthermore, an easy-to-use application has been developed to improve the user experience, so that the operator can interact directly with the robot via a special setting screen. It is possible, using this feature, to modify advanced settings such as voice commands or IP address without having to return back to the code

Kinisi: A Platform for Autonomizing Off-Road Vehicles

This project proposed a modular system that would autonomize off-road vehicles while retaining full manual operability. This MQP team designed and developed a Level 3 autonomous vehicle prototype using an SAE Baja vehicle outfitted with actuators and exteroceptive sensors. At the end of the project, the vehicle had a drive-by-wire system, could localize itself using sensors, generate a map of its surroundings, and plan a path to follow a desired trajectory. Given a map, the vehicle could traverse a series of obstacles in an enclosed environment. The long- term goal is to alter the software system to make it modular and operate in real-time, so the vehicle can autonomously navigate off-road terrain to rescue and aid a distressed individual

Design and development of an Autonomous Mobile Robot (AMR) based on a ROS controller

openAn Autonomous Mobile Robot is a robot that runs and navigates by itself without human intervention. AMRs are foundamental for automating materials handling into warehouses. This thesis work ex- plains the procedure followed for designing and developing an AMR. The hardware components are chosen considering the way in which the robot will be controlled. A layered controlling approach is used. The high-level controller is a mini PC running ROS nodes. The ROS controller manages the actions that drivers have to perform and the data received from sensors. The medium-level controller translates the actions into signals that will be sent to the low-level controllers. The medium-level controller is an Arduino Mega, which sends PWM signals for controlling the speed of two BLDC motor wheels. The low-level controllers are two BLDC motor drivers that power, sense and drive the motor wheels. The Arduino implements a PI controller on the speed of rotation of each motorized wheel. Real tests are per- formed on the robot in order to evaluate the efficiency of the control- ling system. A future implementation consists in an integration of a LiDAR sensor in order to execute a SLAM algorithm, which will allow the robot to move autonomously in a space with obstacles.An Autonomous Mobile Robot is a robot that runs and navigates by itself without human intervention. AMRs are foundamental for automating materials handling into warehouses. This thesis work ex- plains the procedure followed for designing and developing an AMR. The hardware components are chosen considering the way in which the robot will be controlled. A layered controlling approach is used. The high-level controller is a mini PC running ROS nodes. The ROS controller manages the actions that drivers have to perform and the data received from sensors. The medium-level controller translates the actions into signals that will be sent to the low-level controllers. The medium-level controller is an Arduino Mega, which sends PWM signals for controlling the speed of two BLDC motor wheels. The low-level controllers are two BLDC motor drivers that power, sense and drive the motor wheels. The Arduino implements a PI controller on the speed of rotation of each motorized wheel. Real tests are per- formed on the robot in order to evaluate the efficiency of the control- ling system. A future implementation consists in an integration of a LiDAR sensor in order to execute a SLAM algorithm, which will allow the robot to move autonomously in a space with obstacles

Towards Natural Human Control and Navigation of Autonomous Wheelchairs

Approximately 2.2 million people in the United States depend on a wheelchair to assist with their mobility. Often times, the wheelchair user can maneuver around using a conventional joystick. Visually impaired or wheelchair patients with restricted hand mobility, such as stroke, arthritis, limb injury, Parkinson’s, cerebral palsy or multiple sclerosis, prevent them from using traditional joystick controls. The resulting mobility limitations force these patients to rely on caretakers to perform everyday tasks. This minimizes the independence of the wheelchair user. Modern day speech recognition systems can be used to enhance user experiences when using electronic devices. By expanding the motorized wheelchair control interface to include the detection of user speech commands, the independence is given back to the mobility impaired. A speech recognition interface was developed for a smart wheelchair. By integrating navigation commands with a map of the wheelchair’s surroundings, the wheelchair interface is more natural and intuitive to use. Complex speech patterns are interpreted for users to command the smart wheelchair to navigate to specified locations within the map. Pocketsphinx, a speech toolkit, is used to interpret the vocal commands. A language model and dictionary were generated based on a set of possible commands and locations supplied to the speech recognition interface. The commands fall under the categories of speed, directional, or destination commands. Speed commands modify the relative speed of the wheelchair. Directional commands modify the relative direction of the wheelchair. Destination commands require a known location on a map to navigate to. The completion of the speech input processer and the connection between wheelchair components via the Robot Operating System make map navigation possible

Implementing and Tuning an Autonomous Racing Car Testbed

Achieving safe autonomous driving is far from a vision at present days, with many examples like Uber, Google and the most famous of all Tesla, as they successfully deployed self driving cars around the world. Researchers and engineers have been putting tremendous efforts and will continue to do so in the following years into developing safe and precise control algorithms and technologies that will be included in future self driving cars. Besides these well known autonomous car deployments, some focus has also been put into autonomous racing competitions, for example the Roborace. The fact is that although significant progress that has been made, testing on real size cars in real environments requires immense financial support, making it impossible for many research groups to enter the game. Consequently, interesting alternatives appeared, such as the F1 Tenth, which challenges students, researchers and engineers to embrace in a low cost autonomous racing competition while developing control algorithms, that rely on sensors and strategies used in real life applications. This thesis focus on the comparison of different control algorithms and their effectiveness, that are present in a racing aspect of the F1 Tenth competition. In this thesis, efforts were put into developing a robotic autonomous car, relying on Robot Operative System, ROS, that not only meet the specifications from the F1 Tenth rules, but also allowed to establish a testbed for different future autonomous driving research.Obter uma condução autónoma segura está longe de uma visão dos dias de hoje, com exemplos como a Uber, Google e o mais famoso deles todos, a Tesla, que já foram globalmente introduzidos com sucesso. Investigadores e engenheiros têm colocado um empenho tremendo e vão continuar a fazê-lo nos próximos anos, a desenvolver algoritmos de controlo precisos e seguros, bem como tecnologias que serão colocados nos carros autónomos do futuro. Para além destes casos de sucesso bem conhecidos, algum foco tem sido colocado em competições de corridas de carros autónomos, como por exemplo o Roborace. O facto ´e que apesar do progresso significante que tem sido feito, fazer testes em carros reais em cenários verdadeiros, requer grande investimento financeiro, tornando impossível para muitos grupos de investigação investir na área. Consequentemente, apareceram alternativas relevantes, tal como o F1 Tenth, que desafia estudantes, investigadores e engenheiros a aderir a uma competição de baixos custos de corridas autónomas, enquanto desenvolvem algoritmos de controlo, que dependem de sensores e estratégias usadas em aplicações reais. Esta tese foca-se na comparação de diferentes algoritmos de controlo e na eficácia dos mesmos, que estão presentes num cenário de corrida da competição do F1 Tenth. Nesta tese, foram colocados muitos esforços para o desenvolvimento de um carro autónomo robótico, baseado em Robot Operative System, ROS, que não só vai de encontro `as especificações do F1 Tenth, mas que também permita estabelecer uma plataforma para futuras investigações de condução autónoma