{GSoC 2026} Project #10: Agentic Dora: Agent-Driven Robot Control #1516
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Hi, I am interested in the "Agentic Dora" GSoC project idea and wanted to share what I've built so far and get your feedback before finalizing my proposal. I implemented a proof-of-concept that bridges a natural language agent with Dora's dataflow system to control a simulated robot. Here's what it includes:
The agent can handle commands like "move forward for 5 seconds", "turn left", "move in the shape of a square" (LLM plans and executes the full sequence), and "status". Before writing the full proposal I wanted to confirm: is this the right direction? Should the simulation remain PyBullet-based, or is there a preferred robot/simulator? Is the agent framework flexible? And are there specific Dora features you'd like the project to demonstrate? Is there a proposal template that I should follow? You can find, attached to this discussion ,a video demo and the link towards the dedicated github repository! Github Repository: https://github.com/fayezzouari/dora-agent Looking forward to your feedback! |
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The bridge between a natural language agent and Dora's dataflow is right direction. For simulation we don't have a hard preference. One possible Dora's value is showing how nodes can be added or swapped without rewriting the pipeline. There isn't a strict template, but a good proposal should cover: the problem and motivation, your proposed architecture and timeline etc. |
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The bridge between a natural language agent and Dora's dataflow is right direction. For simulation we don't have a hard preference. One possible Dora's value is showing how nodes can be added or swapped without rewriting the pipeline. There isn't a strict template, but a good proposal should cover: the problem and motivation, your proposed architecture and timeline etc.