Walker Byrnes
@walbyr.bsky.social
PhD student at Georgia Tech.
Foundation model planning and reasoning for generalizable autonomy. http://walkerbyrnes.github.io
Foundation model planning and reasoning for generalizable autonomy. http://walkerbyrnes.github.io
We are thrilled to announce that our paper, Language-Guided Continual Learning for Task Planning with Iterative Model Building (CLIMB), was accepted to #ICRA2025!
CLIMB is a robot task planner that builds a world model by iteratively executing and observing tasks.
📃 plan-with-climb.github.io
[1/6]
CLIMB is a robot task planner that builds a world model by iteratively executing and observing tasks.
📃 plan-with-climb.github.io
[1/6]
March 6, 2025 at 10:11 PM
We are thrilled to announce that our paper, Language-Guided Continual Learning for Task Planning with Iterative Model Building (CLIMB), was accepted to #ICRA2025!
CLIMB is a robot task planner that builds a world model by iteratively executing and observing tasks.
📃 plan-with-climb.github.io
[1/6]
CLIMB is a robot task planner that builds a world model by iteratively executing and observing tasks.
📃 plan-with-climb.github.io
[1/6]
Reposted by Walker Byrnes
How can robots reliably place objects in diverse real-world tasks?
🤖🔍 Placement is hard! - objects vary in shape & placement modes (such as stacking, hanging, insertion)
AnyPlace predicts placement poses of unseen objects in real-world with ony using synthetic training data!
Read on👇
🤖🔍 Placement is hard! - objects vary in shape & placement modes (such as stacking, hanging, insertion)
AnyPlace predicts placement poses of unseen objects in real-world with ony using synthetic training data!
Read on👇
February 24, 2025 at 10:11 PM
How can robots reliably place objects in diverse real-world tasks?
🤖🔍 Placement is hard! - objects vary in shape & placement modes (such as stacking, hanging, insertion)
AnyPlace predicts placement poses of unseen objects in real-world with ony using synthetic training data!
Read on👇
🤖🔍 Placement is hard! - objects vary in shape & placement modes (such as stacking, hanging, insertion)
AnyPlace predicts placement poses of unseen objects in real-world with ony using synthetic training data!
Read on👇