Robotics papers

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31 papers found

ReviewPaperPublishedTopics

7.5No Plan, Yet Human: A Reactive Robotics Model Predicts Human Planning Failures on a Clinical TaskThis research bridges robotics and cognitive science, offering insights into human planning processes that could inform both AI development and clinical assessments.Aug 29, 2026Robotics Reasoning

6.5How Should I Pick a Foundation Model for My Robot? In Favor of a Community Evaluation Framework for Social RobotsSelecting the right foundation model is crucial for developing effective social robots, and a structured evaluation framework can guide researchers in making informed choices.Aug 10, 2026Evaluation Robotics

7.5As You Wish: Mission Planning with Formal Verification using LLMs in Precision AgricultureThis work addresses the challenges of operating robotic systems in agriculture by improving the usability and reliability of mission planning through natural language, which could facilitate broader adoption of autonomous technologies in the field.Aug 7, 2026Other

7.5NSF-HRPT: Neural Semantic Field meets Hierarchical Risk Perception Tree for Safety-Critical Scenario AssessmentThis research addresses critical challenges in real-time risk assessment for autonomous systems, which is essential for improving safety in real-world driving scenarios.Aug 6, 2026Safety Robotics Vision Language

7.5Think Short, Defer Smart, Act, and Repeat: Calibrated Reasoning and Uncertainty-Aware Deferral for Edge LLM AgentsThis work addresses the critical challenge of deploying LLM agents in resource-constrained environments, making it relevant for practical applications in robotics and real-time decision-making systems.Jul 31, 2026LLM Agent Reasoning

7.5Towards Trustworthy Embodied Intelligence: A Systems Framework and Graded Trustworthiness LevelsAs embodied AI systems become more prevalent, establishing a clear framework for trustworthiness is crucial for ensuring safety and reliability in real-world applications.Jul 31, 2026Robotics Safety Other

7.2LeAct: Learning to Reason from Expert ActionsThis approach provides a novel way to extract reasoning from expert systems, potentially enhancing the capabilities of AI models in complex domains.Jul 27, 2026Reasoning Agent Robotics

7.0Human-Inspired Neuro-Symbolic World Modeling and Logic Reasoning for Interpretable Safe UAV Landing Site AssessmentThis work is relevant for AI engineers and researchers interested in improving the safety and interpretability of UAV operations in unstructured environments, which is crucial for real-world applications.Jul 20, 2026Reasoning Interpretability Safety

6.8Human-In-The-Loop Machine Learning for Safe and Ethical Autonomous Vehicles: Principles, Challenges, and OpportunitiesUnderstanding how to effectively incorporate human oversight in autonomous vehicle systems is crucial for improving safety, reliability, and ethical compliance in real-world applications.Jul 18, 2026Survey Safety Robotics

7.5Latent Memory Palace: Reasoning for Control as Autoregressive Variational InferenceThis work addresses the challenge of transferring adaptive reasoning capabilities from language models to continuous control, which is crucial for advancing AI applications in robotics and autonomous systems.Jul 10, 2026Agent Reasoning Robotics

7.5Learning social norms enhances compatibility in dynamic human-AI coordinationUnderstanding and integrating social norms into AI systems is crucial for their effective and natural interaction with humans, which is increasingly relevant as AI becomes more prevalent in daily life.Jul 9, 2026Agent Alignment Robotics

7.5CSTutorBench: Benchmarking Small Language Models as Tutors for Block-Based ProgrammingThis research addresses the practical need for effective AI tutors in educational settings, particularly in K-12 environments, where privacy and cost are significant concerns.Jul 8, 2026LLM Evaluation Benchmark

7.8DriveVLM-RL: Neuroscience-Inspired Reinforcement Learning with Vision-Language Models for Safe and Deployable Autonomous DrivingThis research addresses critical safety challenges in autonomous driving by leveraging advanced semantic understanding, making it relevant for both practical applications and further research in the field.Jul 3, 2026Agent Vision Language Safety

7.5EgoSafetyBench: A Diagnostic Egocentric Video Benchmark for Evaluating Embodied VLMs as Runtime Safety GuardsThis research addresses the critical need for effective safety measures in embodied AI systems, which are increasingly deployed in real-world environments.Jul 2, 2026Evaluation Benchmark Vision Language

6.8When Stopping Fails: Rethinking Minimal Risk Conditions through Human-Interactive Autonomous Driving for Safe Transportation SystemsUnderstanding and improving AV interaction with human agents and infrastructure is crucial for the safe and effective deployment of autonomous vehicles in urban settings.Jun 30, 2026Safety Robotics Other

7.5BadRobot: Jailbreaking Embodied LLM Agents in the Physical WorldUnderstanding and mitigating the risks associated with embodied AI systems is crucial for ensuring their safe deployment in real-world applications.Jun 10, 2026LLM Agent Security

6.8Exploration of Foundation Model-Based Robots in Patient and Elderly CareUnderstanding the limitations and potential of foundation model-based robots in healthcare is crucial for developing effective and reliable care technologies as populations age.Jun 10, 2026Robotics Evaluation LLM

6.8Learning of Robot Safety Policies via Adversarial Synthetic ScenariosThis research addresses the critical need for robust safety mechanisms in robots operating in unpredictable real-world environments, which is essential for their safe deployment.Jun 6, 2026Robotics Safety

6.8Safe Embodied AI for Long-horizon Tasks: A Cross-layer Analysis of Robotic ManipulationUnderstanding safety in robotic manipulation is crucial for deploying AI systems in real-world environments where failures can have significant consequences.Jun 6, 2026Robotics Safety Survey

6.8Silent Failures in Physical AI: A Literature Review of Runtime Action Authorization for Autonomous SystemsUnderstanding and mitigating silent failures in autonomous systems is crucial for ensuring the safety and reliability of AI-driven physical actions in real-world applications.Jun 2, 2026Safety Robotics Survey

7.5Reliable Reasoning with Large Language Models via Preference-Based Maximum SatisfiabilityThis research addresses a significant limitation in LLMs' ability to handle complex optimization tasks, making it relevant for applications in robotics and other constraint-heavy domains.May 29, 2026LLM Reasoning Robotics

7.5AnyMo: Scaling Any-Modality Conditional Motion Generation with Masked ModelingThis work addresses the critical challenge of generating human motion across multiple modalities, which is essential for advancements in robotics and computer vision applications.May 29, 2026Multimodal Data Robotics

7.5Robotics-Inspired Guardrails for Foundation Models in Socially Sensitive DomainsAs foundation models are increasingly used in critical areas like education and mental health, ensuring their safe and context-aware operation is essential to prevent harmful outcomes.May 21, 2026Safety Robotics Alignment

6.8Say the Mission, Execute the Swarm: Agent-Enhanced LLM Reasoning in the Web-of-DronesThis research explores the potential of LLMs in real-time UAV swarm management, a growing area of interest in autonomous systems and robotics, highlighting both capabilities and current limitations.May 7, 2026LLM Agent Reasoning

7.0Safety in Embodied AI: A Survey of Risks, Attacks, and DefensesUnderstanding safety in embodied AI is crucial as these systems are increasingly deployed in safety-critical environments like healthcare and transportation.May 7, 2026Survey Safety Security

7.5MILD: Mediator Agent System with Bidirectional Perception and Multi-Layered Alignment for Human-Vehicle CollaborationThis research addresses critical challenges in human-vehicle collaboration, potentially improving safety and user experience in partially automated driving systems.May 6, 2026Agent Alignment Safety

7.5Towards Neuro-symbolic Causal Rule Synthesis, Verification, and Evaluation Grounded in Legal and Safety PrinciplesThis work addresses critical challenges in rule-based systems, particularly in safety-critical domains like autonomous driving, by providing a structured approach to goal specification and rule maintenance.May 1, 2026LLM Agent Safety

7.5Benchmarking the Safety of Large Language Models for Robotic Health Attendant ControlUnderstanding the safety of LLMs in healthcare applications is crucial for ensuring patient safety and effective robotic assistance.Apr 30, 2026LLM Robotics Safety

7.5A Co-Evolutionary Theory of Human-AI Coexistence: Mutualism, Governance, and Dynamics in Complex SocietiesThis research addresses the evolving dynamics of human-AI interactions, offering insights that could inform the design of more effective governance structures in AI systems.Apr 30, 2026Alignment Robotics Other

7.5RL-STPA: Adapting System-Theoretic Hazard Analysis for Safety-Critical Reinforcement LearningAs reinforcement learning is increasingly applied in safety-critical domains, this framework provides a necessary tool for identifying potential hazards that traditional methods overlook.Apr 18, 2026Safety Robotics Evaluation

8.5Agentic Driving Coach: Robustness and Determinism of Agentic AI-Powered Human-in-the-Loop Cyber-Physical SystemsAs AI systems increasingly interact with humans and physical environments, ensuring their reliability and predictability is crucial for safety and effectiveness, particularly in applications like autonomous driving.Apr 14, 2026Agent Other Robotics