Papers Task Planning
“Task Planning” 태그가 달린 논문 344편 · 필터 해제
COHERENT: Collaboration of Heterogeneous Multi-Robot System with Large Language Models
Leveraging the powerful reasoning capabilities of large language models (LLMs), recent LLM-based robot task planning methods yield promising results. However, they mainly focus on single or multiple homogeneous robots on…
Robot Task PlanningTask PlanningAlignBot: Aligning VLM-powered Customized Task Planning with User Reminders Through Fine-Tuning for Household Robots
This paper presents AlignBot, a novel framework designed to optimize VLM-powered customized task planning for household robots by effectively aligning with user reminders. In domestic settings, aligning task planning wit…
Task PlanningLEMMo-Plan: LLM-Enhanced Learning from Multi-Modal Demonstration for Planning Sequential Contact-Rich Manipulation Tasks
Large Language Models (LLMs) have gained popularity in task planning for long-horizon manipulation tasks. To enhance the validity of LLM-generated plans, visual demonstrations and online videos have been widely employed …
Contact-rich ManipulationIn-Context LearningTask PlanningSIFToM: Robust Spoken Instruction Following through Theory of Mind
Spoken language instructions are ubiquitous in agent collaboration. However, in human-robot collaboration, recognition accuracy for human speech is often influenced by various speech and environmental factors, such as ba…
Instruction FollowingTask PlanningP-RAG: Progressive Retrieval Augmented Generation For Planning on Embodied Everyday Task
Embodied Everyday Task is a popular task in the embodied AI community, requiring agents to make a sequence of actions based on natural language instructions and visual observations. Traditional learning-based approaches …
Large Language ModelRAGRetrievalRetrieval-augmented Generation+1Encoding Reusable Multi-Robot Planning Strategies as Abstract Hypergraphs
Multi-Robot Task Planning (MR-TP) is the search for a discrete-action plan a team of robots should take to complete a task. The complexity of such problems scales exponentially with the number of robots and task complexi…
Robot Task PlanningTask PlanningRelevance for Human Robot Collaboration
Inspired by the human ability to selectively focus on relevant information, this paper introduces relevance, a novel dimensionality reduction process for human-robot collaboration (HRC). Our approach incorporates a conti…
Dimensionality ReductionScene UnderstandingTask PlanningScalable Task Planning via Large Language Models and Structured World Representations
Planning methods struggle with computational intractability in solving task-level problems in large-scale environments. This work explores leveraging the commonsense knowledge encoded in LLMs to empower planning techniqu…
Task PlanningEMPOWER: Embodied Multi-role Open-vocabulary Planning with Online Grounding and Execution
Task planning for robots in real-life settings presents significant challenges. These challenges stem from three primary issues: the difficulty in identifying grounded sequences of steps to achieve a goal; the lack of a …
Task PlanningAeroVerse: UAV-Agent Benchmark Suite for Simulating, Pre-training, Finetuning, and Evaluating Aerospace Embodied World Models
Aerospace embodied intelligence aims to empower unmanned aerial vehicles (UAVs) and other aerospace platforms to achieve autonomous perception, cognition, and action, as well as egocentric active interaction with humans …
Spatial ReasoningTask PlanningLLM-enhanced Scene Graph Learning for Household Rearrangement
The household rearrangement task involves spotting misplaced objects in a scene and accommodate them with proper places. It depends both on common-sense knowledge on the objective side and human user preference on the su…
Common Sense ReasoningGraph LearningTask PlanningAutonomous Behavior Planning For Humanoid Loco-manipulation Through Grounded Language Model
Enabling humanoid robots to perform autonomously loco-manipulation in unstructured environments is crucial and highly challenging for achieving embodied intelligence. This involves robots being able to plan their actions…
Decision MakingLanguage ModelingLanguage ModellingTask PlanningNl2Hltl2Plan: Scaling Up Natural Language Understanding for Multi-Robots Through Hierarchical Temporal Logic Task Representation
To enable non-experts to specify long-horizon, multi-robot collaborative tasks, language models are increasingly used to translate natural language commands into formal specifications. However, because translation can oc…
Natural Language UnderstandingRobot Task PlanningSentenceTask Planning+1General-purpose Clothes Manipulation with Semantic Keypoints
Clothes manipulation is a critical capability for household robots; yet, existing methods are often confined to specific tasks, such as folding or flattening, due to the complex high-dimensional geometry of deformable fa…
Action GenerationLanguage ModelingLanguage ModellingLarge Language Model+1Plan with Code: Comparing approaches for robust NL to DSL generation
Planning in code is considered a more reliable approach for many orchestration tasks. This is because code is more tractable than steps generated via Natural Language and make it easy to support more complex sequences by…
Code GenerationHallucinationRAGRetrieval-augmented Generation+1Retrieval-Augmented Hierarchical in-Context Reinforcement Learning and Hindsight Modular Reflections for Task Planning with LLMs
Large Language Models (LLMs) have demonstrated remarkable abilities in various language tasks, making them promising candidates for decision-making in robotics. Inspired by Hierarchical Reinforcement Learning (HRL), we p…
Decision MakingHierarchical Reinforcement LearningIn-Context LearningIn-Context Reinforcement Learning+4Multi-Agent Planning Using Visual Language Models
Large Language Models (LLMs) and Visual Language Models (VLMs) are attracting increasing interest due to their improving performance and applications across various domains and tasks. However, LLMs and VLMs can produce e…
Task PlanningEARBench: Towards Evaluating Physical Risk Awareness for Task Planning of Foundation Model-based Embodied AI Agents
Embodied artificial intelligence (EAI) integrates advanced AI models into physical entities for real-world interaction. The emergence of foundation models as the "brain" of EAI agents for high-level task planning has sho…
Scene GenerationTask PlanningTowards Coarse-grained Visual Language Navigation Task Planning Enhanced by Event Knowledge Graph
Visual language navigation (VLN) is one of the important research in embodied AI. It aims to enable an agent to understand the surrounding environment and complete navigation tasks. VLN instructions could be categorized …
Language ModellingLarge Language ModelTask PlanningEPD: Long-term Memory Extraction, Context-awared Planning and Multi-iteration Decision @ EgoPlan Challenge ICML 2024
In this technical report, we present our solution for the EgoPlan Challenge in ICML 2024. To address the real-world egocentric task planning problem, we introduce a novel planning framework which comprises three stages: …
Decision MakingTask Planning