Complete project overview, solution, technologies, and timeline.
The overall problem that REACH is in charge of is that robotic arms aren't designed well enough to handle the complexity of a regular human limb
Some context to this problem is that robotic arms are too rigid: they use hardcoded movements that break down in dynamic environments and that there isnt an anything out there that addresses this issue in its real-world use. - Impact on the sponsor's business
The solution that REACH has come up with for this is problem is the creation of a simluation-based reinforced-learning framework, which is expected to allow a robotic arm to learn and later assist with daily task, while being smooth, responsive, and have energy-efficient assistance.
Original Project Proposal: View the initial concept provided by our sponsor
for this project, a few requirements are needed:
Our techinal solution is the creation of a sim-base, reinforced-learning framework.
This framework allows for the robotic arm to learn from its actions and self-improve while giving assistance to those that have upper limb disabilities. This will also use YOLO, a camere, to detect and operate with visual data within its environment.
Why we chose it: The reason why this language was chosen was it was the recommended language we'd use by the clients in order to accomplished the framework for this project.
Role in project: Python's role in this project is to be used in making a framework with reinforced-learning in order to later help operate a robotic arm which is attached at the waist.