Multimodal Dexterous Hand Researcher
Found in: Appcast Linkedin GBL C2 - 2 weeks ago
Job Description:
Using robots for vehicle testing provides an invaluable potential for car manufacturers to optimize their products' quality, safety and efficiency. The purpose of this project is to design and develop a cost-effective, modular, virtual and physical combined platform that can evaluate and optimize the performance of general-purpose robotic arms and dexterous hands in various vehicle-centric use cases such as door and window operation, seat adjustment, steering wheel and break manipulation, and potentially other in-vehicle tasks. This platform will allow developers to iterate on hardware components, AI algorithms, and control systems, facilitating seamless transition from simulation to real-world deployment.
Responsibilities:
1. Develop visual feedback processing algorithms to monitor the dexterous hand's actions and adjust them if necessary.
2. Integrate torque and visual feedback systems seamlessly into the overall dexterous hand control system.
3. Conduct regular testing and debugging to improve the stability of the systems.
4. Collaborate with cross-functional teams to ensure seamless integration of all components.
5. Document all processes and procedures related to the development of the systems.
Requirements:
1. Master/PhD students in Computer Science, Robotic Engineering, or related field.
2. Strong knowledge of robotic arm/dexterous hand control systems and feedback mechanisms.
3. Experience with torque feedback processing and visual feedback systems.
4. Proficiency in programming languages such as Python, C/C++.
5. Strong communication skills and ability to work effectively in a team environment.
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