This paper proposes RL-MACRO, a cybernetic closed-loop intelligence framework for autonomous robotic craniotomy, which includes a CNN-LSTM observer for temperature reconstruction, an offline Implicit…

BORA is an offline-to-online RL framework that enhances dexterous VLA models for real-world robotics by using an action-conditioned critic and a lightweight residual adaptation mechanism to correct ex…

This paper presents a robot-agnostic compliant-control framework with standardized interfaces for ROS control ecosystem, enabling reusable infrastructure for various manipulators and diverse compliant…

The paper proposes a novel attack paradigm demonstrating how compromising a single robot in an LLM-controlled multi-robot system can rapidly propagate malicious intent to cause coordinated unsafe acti…

ASPIRE is a continual learning system that autonomously writes and refines robot control programs in a code-as-policy paradigm, discovering transferable skills and surpassing prior methods on various…

This paper proposes coupled egocentric control, a body-following teleoperation approach for whole-body robot control, improving efficiency, reducing effort, and increasing ease of use.

A two-layer framework using a large language model for force-conditioned reinforce learning with recovery maneuvers and force signatures.

The paper demonstrates a semantic denial-of-service attack against LLM-controlled robots by injecting short, safety-plausible phrases into the audio channel, causing the robot to halt or disrupt execu…

The paper argues that the Authorization-Execution Gap (AEG)—the divergence between intended authorization and actual execution—is a critical safety and security flaw in open-world agents, requiring so…

This paper presents Mana, a sim-to-real framework for dexterous articulated tool manipulation.

The paper introduces RoboJailBench, the first standardized evaluation framework for assessing adversarial jailbreak attacks and defenses in embodied AI systems like robots.

The paper provides a holistic threat model for LLM-enabled robotic systems by analyzing how conventional, adversarial, and conversational threats propagate across the entire perception-planning-actuat…

This paper provides a systematic survey of ROS 2 middleware and identifies architectural limits through three dimensions: Space, Time, and State.

A framework called AERMANI-PLACE is presented for language-guided object placement with aerial manipulators using image editing and depth observations.

This paper presents a system-level framework to mitigate collisions and improve retargeting of sign language generation outputs for humanoid robot execution.

The paper proposes SafeClaw-R, a novel framework that enforces safety as a system-level invariant over the execution graph to mitigate the high safety and security risks inherent in autonomous multi-a…