Zero-Shot Interactive Personalized Robot Navigation Framework: ORION

แนวคิดหลัก

Introducing Zero-shot Interactive Personalized Object Navigation (ZIPON) and the ORION framework for personalized robot navigation.

บทคัดย่อ

Introduction to ZSON: Recent advancements in Zero-Shot Object Navigation (ZSON) for robots.
Limitations of ZSON: Lack of user feedback consideration in instruction-following tasks.
ZIPON Introduction: Introducing Zero-shot Interactive Personalized Object Navigation (ZIPON) for personalized goal objects.
ORION Framework: Description of the Open-woRld Interactive persOnalized Navi-gation (ORION) framework using Large Language Models (LLMs).
Experimental Results: Performance improvements with user feedback types in simulated and real-world environments.
Comparison with Baselines: Comparison with existing methods like CoW, VLMap, and CF.
Evaluation Metrics: Success Rate (SR), Success Rate weighted by Path Length (SPL), and Success Rate weighted by Interaction Turns (SIT).
Ablation Study: Impact analysis of different modules on ORION's performance.

สถิติ

"Experimental results show that the performance of interactive agents that can leverage user feedback exhibits significant improvement."
"Our empirical results have shown that agents that can communicate and leverage diverse user feedback significantly improve their success rates."

คำพูด

"Instruction-following often involves back-and-forth interaction to reduce uncertainties, correct mistakes, and handle exceptions."
"Agents need to elicit and leverage language feedback from users during task execution to avoid errors and achieve the goal."

ข้อมูลเชิงลึกที่สำคัญจาก

Think, Act, and Ask

by Yinpei Dai,R... ที่ arxiv.org 03-20-2024

https://arxiv.org/pdf/2310.07968.pdf

สอบถามเพิ่มเติม

How can personalized robot navigation impact daily human activities?

Personalized robot navigation can have a significant impact on daily human activities by enhancing the efficiency and effectiveness of tasks that involve human-robot interactions. For example, in household settings, a robot equipped with personalized navigation capabilities could assist individuals in locating specific items or objects based on unique identifiers such as names or descriptions. This could streamline everyday tasks like finding personal belongings, organizing spaces, or even assisting with reminders for important items.
Moreover, personalized robot navigation can improve user experience and satisfaction by tailoring interactions to individual preferences. By understanding user-specific needs and providing customized assistance, robots can offer more intuitive and efficient support in various scenarios. This level of personalization not only enhances the functionality of robots but also fosters better communication and collaboration between humans and machines.

What are potential drawbacks of relying heavily on user feedback for robot navigation?

While user feedback is essential for improving the performance of robots in interactive tasks like navigation, there are several potential drawbacks associated with relying heavily on this feedback:

Subjectivity: User feedback may vary based on individual perceptions, preferences, or communication styles. Relying solely on subjective input can introduce inconsistencies or biases into the decision-making process of robots.

Dependency: Excessive reliance on user feedback may lead to overdependence on external guidance, limiting the autonomy and adaptability of robots in dynamic environments where real-time decisions are crucial.

Misinterpretation: Robots interpreting ambiguous or inaccurate feedback from users could result in incorrect actions or responses, leading to suboptimal outcomes in navigation tasks.

Feedback Loop: Continuous loops of interaction for clarification or correction purposes might slow down task completion rates and increase cognitive load for both users and robots.

Privacy Concerns: Gathering extensive user feedback raises privacy concerns regarding data collection and storage practices that need to be addressed to ensure ethical use of personal information.

How can the concept of personalized robot navigation be applied to other fields beyond robotics?

The concept of personalized robot navigation has broader applications beyond robotics across various domains:

Healthcare: Personalized robotic assistants could navigate hospital environments efficiently while considering patient-specific requirements such as room locations, medical history details stored securely within hospital systems.

Retail: In retail settings, autonomous shopping bots using personalized navigation could guide customers through stores based on their shopping lists or preferences gathered from loyalty programs.

Tourism: Personalized tour guide robots equipped with advanced navigational abilities could provide tailored experiences by adapting routes based on visitors' interests or accessibility needs.

4 .Smart Homes: Home automation systems incorporating personalized navigational features enable smart devices to move autonomously within homes according to residents' schedules/preferences.
5 .Logistics: Autonomous delivery drones/vehicles utilizing personalized routing algorithms enhance efficiency by considering recipient addresses/preferences when navigating urban landscapes.
These applications demonstrate how incorporating elements of personalization into robotic systems extends their utility beyond traditional robotics contexts into diverse sectors where tailored interactions play a crucial role in enhancing overall experiences and outcomes..