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Found 8 papers, 0 papers with code
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
In each iteration, the image is annotated with a visual representation of proposals that the VLM can refer to (e. g., candidate robot actions, localizations, or trajectories).
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator
For example, consider prompting an LM to write code that counts the number of times it detects sarcasm in an essay: the LM may struggle to write an implementation for "detect_sarcasm(string)" that can be executed by the interpreter (handling the edge cases would be insurmountable).
Inner Monologue: Embodied Reasoning through Planning with Language Models
We investigate a variety of sources of feedback, such as success detection, scene description, and human interaction.
Learning to Compose Hierarchical Object-Centric Controllers for Robotic Manipulation
Manipulation tasks can often be decomposed into multiple subtasks performed in parallel, e. g., sliding an object to a goal pose while maintaining contact with a table.
DexPilot: Vision Based Teleoperation of Dexterous Robotic Hand-Arm System
Teleoperation offers the possibility of imparting robotic systems with sophisticated reasoning skills, intuition, and creativity to perform tasks.
Towards Precise Robotic Grasping by Probabilistic Post-grasp Displacement Estimation
Precise robotic grasping is important for many industrial applications, such as assembly and palletizing, where the location of the object needs to be controlled and known.
GPU-Accelerated Robotic Simulation for Distributed Reinforcement Learning
Most Deep Reinforcement Learning (Deep RL) algorithms require a prohibitively large number of training samples for learning complex tasks.
Robotics
Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics
To reduce data collection time for deep learning of robust robotic grasp plans, we explore training from a synthetic dataset of 6. 7 million point clouds, grasps, and analytic grasp metrics generated from thousands of 3D models from Dex-Net 1. 0 in randomized poses on a table.
Robotics
