Papers Task Planning
“Task Planning” 태그가 달린 논문 344편 · 필터 해제
WorkR: Occupation Inference for Intelligent Task Assistance
Occupation information can be utilized by digital assistants to provide occupation-specific personalized task support, including interruption management, task planning, and recommendations. Prior research in the digital …
ManagementTask PlanningWonderful Team: Zero-Shot Physical Task Planning with Visual LLMs
We introduce Wonderful Team, a multi-agent Vision Large Language Model (VLLM) framework for executing high-level robotic planning in a zero-shot regime. In our context, zero-shot high-level planning means that for a nove…
Action GenerationLarge Language ModelTask PlanningVisual ReasoningDISCO: Embodied Navigation and Interaction via Differentiable Scene Semantics and Dual-level Control
Building a general-purpose intelligent home-assistant agent skilled in diverse tasks by human commands is a long-term blueprint of embodied AI research, which poses requirements on task planning, environment modeling, an…
Instruction FollowingNavigateTask PlanningVision-Language NavigationAgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases
LLM agents have demonstrated remarkable performance across various applications, primarily due to their advanced capabilities in reasoning, utilizing external knowledge and tools, calling APIs, and executing actions to i…
Autonomous DrivingBackdoor AttackRAGRed Teaming+2BadRobot: Jailbreaking Embodied LLMs in the Physical World
Embodied AI represents systems where AI is integrated into physical entities. Large Language Model (LLM), which exhibits powerful language understanding abilities, has been extensively employed in embodied AI by facilita…
Language ModelingLanguage ModellingLarge Language ModelTask PlanningAn Optimal Task Planning and Agent-aware Allocation Algorithm in Collaborative Tasks Combining with PDDL and POPF
Industry 4.0 proposes the integration of artificial intelligence (AI) into manufacturing and other industries to create smart collaborative systems which enhance efficiency. The aim of this paper is to develop a flexible…
Task PlanningThis&That: Language-Gesture Controlled Video Generation for Robot Planning
Clear, interpretable instructions are invaluable when attempting any complex task. Good instructions help to clarify the task and even anticipate the steps needed to solve it. In this work, we propose a robot learning fr…
Task PlanningVideo GenerationAffordances-Oriented Planning using Foundation Models for Continuous Vision-Language Navigation
LLM-based agents have demonstrated impressive zero-shot performance in vision-language navigation (VLN) task. However, existing LLM-based methods often focus only on solving high-level task planning by selecting nodes in…
Decision MakingMotion PlanningTask PlanningVision-Language NavigationMFE-ETP: A Comprehensive Evaluation Benchmark for Multi-modal Foundation Models on Embodied Task Planning
In recent years, Multi-modal Foundation Models (MFMs) and Embodied Artificial Intelligence (EAI) have been advancing side by side at an unprecedented pace. The integration of the two has garnered significant attention fr…
Embodied Question AnsweringQuestion AnsweringTask PlanningMARLIN: A Cloud Integrated Robotic Solution to Support Intralogistics in Retail
In this paper, we present the service robot MARLIN and its integration with the K4R platform, a cloud system for complex AI applications in retail. At its core, this platform contains so-called semantic digital twins, a …
Autonomous NavigationTask PlanningMMRo: Are Multimodal LLMs Eligible as the Brain for In-Home Robotics?
It is fundamentally challenging for robots to serve as useful assistants in human environments because this requires addressing a spectrum of sub-problems across robotics, including perception, language understanding, re…
Task PlanningVisual ReasoningDKPROMPT: Domain Knowledge Prompting Vision-Language Models for Open-World Planning
Vision-language models (VLMs) have been applied to robot task planning problems, where the robot receives a task in natural language and generates plans based on visual inputs. While current VLMs have demonstrated strong…
Robot Task PlanningTask PlanningAutomating Transfer of Robot Task Plans using Functorial Data Migrations
This paper introduces a novel approach to ontology-based robot plan transfer by leveraging functorial data migrations, a structured mapping method derived from category theory. Functors provide structured maps between pl…
Task PlanningDiffusion-Based Failure Sampling for Evaluating Safety-Critical Autonomous Systems
Validating safety-critical autonomous systems in high-dimensional domains such as robotics presents a significant challenge. Existing black-box approaches based on Markov chain Monte Carlo may require an enormous number …
DenoisingTask PlanningEmbodied Instruction Following in Unknown Environments
Enabling embodied agents to complete complex human instructions from natural language is crucial to autonomous systems in household services. Conventional methods can only accomplish human instructions in the known envir…
Instruction FollowingTask PlanningDetails Make a Difference: Object State-Sensitive Neurorobotic Task Planning
The state of an object reflects its current status or condition and is important for a robot's task planning and manipulation. However, detecting an object's state and generating a state-sensitive plan for robots is chal…
Dense CaptioningObjectTask PlanningDAG-Plan: Generating Directed Acyclic Dependency Graphs for Dual-Arm Cooperative Planning
Dual-arm robots offer enhanced versatility and efficiency over single-arm counterparts by enabling concurrent manipulation of multiple objects or cooperative execution of tasks using both arms. However, the coordination …
Task PlanningRS-Agent: Automating Remote Sensing Tasks through Intelligent Agent
The unprecedented advancements in Multimodal Large Language Models (MLLMs) have demonstrated strong potential in interacting with humans through both language and visual inputs to perform downstream tasks such as visual …
AI AgentDescriptiveInstruction FollowingLanguage Modeling+10NYU CTF Bench: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security
Large Language Models (LLMs) are being deployed across various domains today. However, their capacity to solve Capture the Flag (CTF) challenges in cybersecurity has not been thoroughly evaluated. To address this, we dev…
Task PlanningVulnerability DetectionTool-Planner: Task Planning with Clusters across Multiple Tools
Large language models (LLMs) have demonstrated exceptional reasoning capabilities, enabling them to solve various complex problems. Recently, this ability has been applied to the paradigm of tool learning. Tool learning …
Language ModellingLarge Language ModelTask Planning