6 accepted papers
This paper presents GLaMP, a grounded language model-based multi-agent framework for long-horizon robotic task planning in industrial environments. A key challenge in such tasks lies in the gap between high-level language reasoning and low-level perceptual grounding, which often leads to error accum…
Enabling robotic systems to perform long-horizon manipulation planning in real-world environments based on multimodal embodied perception and comprehension remains a longstanding challenge. Recent advancements in large language models (LLMs) have spurred the development of LLM-based planners; howeve
Soft optical sensors are an exciting sensing technology for capturing the deformation of soft structures as they can easily fabricated and integrated. However, one key challenge is their scalability, as each fiber requires a sensor, and to achieve large area, or multi-fiber sensing requires many opt
Knowledge-based visual question answering (KVQA) has been extensively studied to answer visual questions with external knowledge, e.g., knowledge graphs (KGs). While several attempts have been proposed to leverage large language models (LLMs) as an implicit knowledge source, it remains challenging s…
Human-robot collaboration (HRC) has been considered as a promising paradigm towards futuristic human-centric smart manufacturing, to meet the thriving needs of mass personalization. In this context, existing robotic systems normally adopt a single-granularity semantic segmentation scheme for environ…
We developed a foot interface enabling an operator to control a robotic arm with four degrees of freedom in continuous direction and speed, for operating one of the multiple tools required during robot-aided surgery. In this letter, we first test whether this pedal interface can be used to carry out