Overview
The IROS 2019 Workshop titled “Open-Ended Learning for Object Perception and Grasping” invites researchers to submit their extended abstracts and papers. This workshop aims to explore the current successes and future challenges in the field of robotics, particularly focusing on enhancing the autonomy of service robots in human-centric environments.
Background & Relevance
In the realm of robotics, object perception and grasping are critical tasks that require robots to operate effectively in dynamic and unpredictable settings. The concept of open-ended learning is pivotal, as it allows robots to continuously adapt and learn from their experiences over time. This approach mirrors human cognitive processes, where individuals learn to recognize and categorize objects based on ongoing interactions with their environment. By fostering open-ended learning, researchers aim to improve how robots perceive and manipulate objects, ultimately leading to better integration into society.
Key Details
- Workshop Date: 8 November 2019
- Submission Deadline: 20 September 2019
- Notification of Acceptance: 1 October 2019
- Location: The Venetian Macao, Macau, China
- Workshop URL: IROS 2019 Workshop
Eligibility & Participation
This workshop is targeted at researchers and practitioners in the field of robotics, particularly those focusing on object perception and grasping. Participants are encouraged to share their innovative ideas and findings related to open-ended learning in robotics.
Submission or Application Guidelines
Submissions are accepted in two categories:
– Extended Abstract: Maximum of 2 pages, focusing on new ideas or late-breaking results related to task-informed grasping.
– Full Paper: Maximum of 6 pages, evaluated based on quality, originality, and relevance to the workshop. All submissions must adhere to IEEE formatting guidelines and should not be under consideration for publication elsewhere.
To submit, email your paper to oel.workshop@gmail.com by the specified deadline.
Additional Context / Real-World Relevance
The integration of open-ended learning in robotics is crucial for developing systems that can operate autonomously in diverse environments. This workshop will address significant challenges, such as knowledge transfer, lifelong learning, and the avoidance of catastrophic forgetting, which are essential for advancing robotic capabilities in real-world applications.
Conclusion
This workshop presents an excellent opportunity for researchers to contribute to the evolving field of robotics. Interested participants should prepare their submissions and engage with the community to share insights and advancements in open-ended learning for object perception and grasping.
Category: CFP & Deadlines
Tags: robotics, open-ended learning, object perception, grasping, cognitive robotics, deep learning, lifelong learning, human-robot interaction
