From Woofs to Words: Towards Intelligent Robotic Guide Dogs with Verbal Communication

Assistive robotics is an important subarea of robotics that focuses on the well-being of people with disabilities. A robotic guide dog is an assistive quadruped robot that helps visually impaired people in obstacle avoidance and navigation. Enabling language capabilities for robotic guide dogs goes beyond naively adding an existing dialog system onto a mobile robot. The novel challenges include grounding language in the dynamically changing environment and improving spatial awareness for the human handler. To address those challenges, we develop a novel dialog system for robotic guide dogs that uses LLMs to verbalize both navigational plans and scenes. The goal is to enable verbal communication for collaborative decision-making within the handler-robot team. In experiments, we conducted a human study to evaluate different verbalization strategies and a simulation study to assess the efficiency and accuracy in navigation tasks.

PROTEA: Securing Robot Task Planning and Execution

Robots need task planning methods to generate action sequences for complex tasks. Recent work on adversarial attacks has revealed significant vulnerabilities in existing robot task planners, especially those built on foundation models. In this paper, we aim to address these security challenges by introducing PROTEA, an LLM-as-a-Judge defense mechanism, to evaluate the security of task plans. PROTEA is developed to address the dimensionality and history challenges in plan safety assessment. We used different LLMs to implement multiple versions of PROTEA for comparison purposes. For systemic evaluations, we created a dataset containing both benign and malicious task plans, where the harmful behaviors were injected at varying levels of stealthiness. Our results provide actionable insights for robotic system practitioners seeking to enhance robustness and security of their task planning systems. Details, dataset and demos are provided: https://protea-secure.github.io/PROTEA/