The digital code driven autonomous synthesis of ibuprofen automated in a 3D-printer-based robot

An automated synthesis robot was constructed by modifying an open source 3D printing platform. The resulting automated system was used to 3D print reaction vessels (reactionware) of differing internal volumes using polypropylene feedstock via a fused deposition modeling 3D printing approach and subsequently make use of these fabricated vessels to synthesize the nonsteroidal anti-inflammatory drug ibuprofen via a consecutive one-pot three-step approach. The synthesis of ibuprofen could be achieved on different scales simply by adjusting the parameters in the robot control software. The software for controlling the synthesis robot was written in the python programming language and hard-coded for the synthesis of ibuprofen by the method described, opening possibilities for the sharing of validated synthetic ‘programs’ which can run on similar low cost, user-constructed robotic platforms towards an ‘open-source’ regime in the area of chemical synthesis

Affordable mobile robotic platforms for teaching computer science at African universities

Educational robotics can play a key role in addressing some of the challenges faced by higher education in Africa. One of the major obstacles preventing a wider adoption of initiatives involving educational robotics in this part of the world is lack of robots that would be affordable by African institutions. In this paper, we present a survey and analysis of currently available affordable mobile robots and their suitability for teaching computer science at African universities. To this end, we propose a set of assessment criteria and review a number of platforms costing an order of magnitude less than the existing popular educational robots. Our analysis identifies suitable candidates offering contrasting features and benefits. We also discuss potential issues and promising directions which can be considered by both educators in Africa but also designers and manufacturers of future robot platforms

Integrating Robotics into First-Year Experience Courses

Robotics are a popular component of many introductory engineering and computer science courses. At Southern Adventist University, the School of Computing faculty decided to integrate robotics into a discipline-specific section of the University’s first-year experience course. The integration of robotics into a first-year experience course has created a hands-on introduction to college life within the Computing discipline while introducing students to the problem-solving process. This paper will introduce a very low-cost robotic platform kit ($50-75) that has been developed for the first-year experience course. Student assessment data from the first offering of this course with the SouthernBot 2.0 kit shows that overall, students were engaged in the open-ended design projects completed during the building of the robot platform

Online Visual Robot Tracking and Identification using Deep LSTM Networks

Collaborative robots working on a common task are necessary for many applications. One of the challenges for achieving collaboration in a team of robots is mutual tracking and identification. We present a novel pipeline for online visionbased detection, tracking and identification of robots with a known and identical appearance. Our method runs in realtime on the limited hardware of the observer robot. Unlike previous works addressing robot tracking and identification, we use a data-driven approach based on recurrent neural networks to learn relations between sequential inputs and outputs. We formulate the data association problem as multiple classification problems. A deep LSTM network was trained on a simulated dataset and fine-tuned on small set of real data. Experiments on two challenging datasets, one synthetic and one real, which include long-term occlusions, show promising results.Comment: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, Canada, 2017. IROS RoboCup Best Paper Awar

Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

The Creation of a low-cost, reliable platform for mobile robotics research

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, June 2011."June 2011." Cataloged from PDF version of thesis.Includes bibliographical references (p. 29).This work documents the planning process, design, fabrication, and integration of a low-cost robot designed for research on the problem of life-long robot mapping. The robotics platform used is the iRobot Create. This robot also employs the PrimeSensor, a sensor with the ability to provide a pixel-matched, colored depth field in real time. This sensor was later purchased by Microsoft and leveraged in their popular gaming device, the Microsoft Kinect. The robot has a powerful Acer Aspire 1830T-6651 laptop with an Intel Core i5 to perform processor-intensive, real-time image processing. The actual construction of the robot consisted of two phases: the physical integration of the components on a chassis and the software integration through the computer. The physical integration is mainly a central chassis made from laser-cut acrylic. This chassis is capable of securely holding the laptop computer in place and provides an elevated mount for the PrimeSensor. This mount has the ability to change the viewing angle of the sensor and lock that angle at 5' increments using a pin. The software integration was completed using open-source packages for the Robot Operating System (ROS) developed by Brown University and a not-for-profit company called OpenNI. These packages were installed on the onboard laptop and the ROS core functions running on the laptop provide the foundation to run new code on this testing platform. This robot is low in cost and provides a reliable, robust, and versatile platform for visionbased artificial intelligence research. The mapping software and vision algorithms developed on this platform will contribute to the development of more intelligent and meaningful vision capabilities for tomorrow's robots.by Taylor Harrison Gilbert.S.B

Build Your Own Robot Friend: An Open-Source Learning Module for Accessible and Engaging AI Education

As artificial intelligence (AI) is playing an increasingly important role in our society and global economy, AI education and literacy have become necessary components in college and K-12 education to prepare students for an AI-powered society. However, current AI curricula have not yet been made accessible and engaging enough for students and schools from all socio-economic backgrounds with different educational goals. In this work, we developed an open-source learning module for college and high school students, which allows students to build their own robot companion from the ground up. This open platform can be used to provide hands-on experience and introductory knowledge about various aspects of AI, including robotics, machine learning (ML), software engineering, and mechanical engineering. Because of the social and personal nature of a socially assistive robot companion, this module also puts a special emphasis on human-centered AI, enabling students to develop a better understanding of human-AI interaction and AI ethics through hands-on learning activities. With open-source documentation, assembling manuals and affordable materials, students from different socio-economic backgrounds can personalize their learning experience based on their individual educational goals. To evaluate the student-perceived quality of our module, we conducted a usability testing workshop with 15 college students recruited from a minority-serving institution. Our results indicate that our AI module is effective, easy-to-follow, and engaging, and it increases student interest in studying AI/ML and robotics in the future. We hope that this work will contribute toward accessible and engaging AI education in human-AI interaction for college and high school students.Comment: Accepted to the Proceedings of the AAAI Conference on Artificial Intelligence (2024