General Overview ICRA 2024 brought together world’s best Robotics research and researchers together and enabled knowledge exchange, science communication, and sharing of the latest research in several sub-fields of robotics. As a Master’s student enhancing legged locomotion research using learning-based methods for challenging terrains, it was a pleasure to witness latest updates on the ongoing work in the field of Legged Robotics, Reinforcement Learning, and a popular emerging topic in the field: loco-manipulation.

This post will briefly cover: Learnings Tasks done and blogs / weekly updates Offline Voice Agent for AGL This report is a requirement of the Final Evaluations phase of Google Summer of Code program. I worked with the Linux Foundation, under Automotive Grade Linux on the project to An Offline voice-agent for Automotive Grade Linux. The proposal for the project can be found here. The Linux Foundation is the nonprofit consortium dedicated to fostering the growth of Linux.

This post will briefly cover: Learnings Tasks done, and those in progress Helpful resources For the project proposal, visit here. Create Recipe for python based Vosk websocket server: GitHub Repo: https://github.com/alphacep/vosk-server/tree/master/websocket Recipe created: python3-vosk-websocket-server_got.bb 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 DESCRIPTION = "WebSocket, gRPC and WebRTC speech recognition server based on Vosk and Kaldi libraries" SUMMARY = "This is a server for highly accurate offline speech recognition using Kaldi and Vosk-API.

– This post will briefly cover: Learnings Tasks done, and those in progress Helpful resources For the project proposal, visit here. Creating the Recipes for a successful build of Vosk Library: In order to integrate Vosk into AGL we need to build it from scratch. The instructions are mentioned in the Vosk Website under “Compilation from source”. As mentioned, the compilation is not straighforward and includes several nuances. As listed in the Dockerfile for vosk-api, and the Dockerfile for vosk-server, the below steps outline the libraries that were required to be built for vosk-api, and the corresponding recipes:

This post will briefly cover: Learnings Tasks done, and those in progress Helpful resources For the project proposal, visit here. This post is in continuation with the previous one, which had been updated as well. Gathering the Vosk API from GitHub: Used devtool to get the Vosk offline speech recognition API from GitHub: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 $ devtool add python3-vosk --src-subdir python --srcrev b1b216d4c87d708935f1601287fe502aa11ee4a9 --version 0.

This post will briefly cover: Learnings Build issue on personal machine, and solving it Identifying dependencies Tasks done, and those in progress Useful resources For the project proposal, visit here. Build issue on personal machine: While building a fresh AGL image on my personal machine, I encountered errors as listed: 1 2 3 4 Summary: 2 tasks failed: virtual:native:/home/aman/AGL/marlin/external/poky/meta/recipes-devtools/llvm/llvm_git.bb:do_compile /home/aman/AGL/marlin/external/meta-openembedded/meta-oe/dynamic-layers/meta-python/recipes-extended/mozjs/mozjs_60.9.0.bb:do_compile Summary: There were 3 ERROR messages shown, returning a non-zero exit code.