28 citations · 51 across the 17 of their papers we have counts for
20 papers
MIND: Instruction-Conditioned Incremental Grounding for Robots
Mohamed Abouagour, Junhyun Nam, Wonse Jo +1
Robots following persistent language instructions must decide which cached room judgments remain valid as their environment changes. We present MIND (Maintenance via INstruction-co…
Toward Study on the Effects of Robot's Humorous Apology on Human's Trust Recovery
Gayoung Kim, Go-Eum Cha, Wonse Jo
Robot errors can disrupt human-robot collaboration by reducing user trust and willingness to rely on the robot. Robot apologies can support trust recovery after such errors, but th…
Human-in-the-Loop Neuro-Symbolic Drift Anticipation for Reliable Visual SLAM
Junhyun Nam, Wonse Jo
This paper introduces Hybrid DeepSEE (HDS), a Human-in-the-Loop (HITL) neuro-symbolic framework for proactive drift anticipation in Visual SLAM (V-SLAM). While data-driven models o…
Establishing a Dynamic Multimodal HRI Dataset for Engagement Analysis with a Humanoid Robot
Buwan Kim, Wonse Jo
This paper presents an experimental design for constructing a multimodal dataset to analyze user engagement in human-robot interaction (HRI). Prior studies have mainly relied on ob…
Pre-Execution Safety Gate & Task Safety Contracts for LLM-Controlled Robot Systems
Ike Obi, Vishnunandan L. N. Venkatesh, Weizheng Wang +5
Large Language Models (LLMs) are increasingly used to convert task commands into robot-executable code, however this pipeline lacks validation gates to detect unsafe and defective…
SafePlan: Leveraging Formal Logic and Chain-of-Thought Reasoning for Enhanced Safety in LLM-based Robotic Task Planning
Ike Obi, Vishnunandan L. N. Venkatesh, Weizheng Wang +5
Robotics researchers increasingly leverage large language models (LLM) in robotics systems, using them as interfaces to receive task commands, generate task plans, form team coalit…