Non Humanoid Robot
Non-humanoid robots encompass a diverse range of designs, from multi-legged robots inspired by insects to wheeled and even flapping-wing robots, all aiming to achieve efficient and adaptable locomotion and manipulation in various environments. Current research emphasizes improving robot autonomy through reinforcement learning, particularly for gait generation and task planning, often incorporating large language models (LLMs) for natural language instruction processing and human-robot interaction. These advancements are significant for expanding robotic capabilities in challenging tasks such as cooking, search and rescue, and collaborative assembly, ultimately impacting fields ranging from manufacturing and healthcare to exploration and disaster response.
Papers
Harmonic Mobile Manipulation
Ruihan Yang, Yejin Kim, Rose Hendrix, Aniruddha Kembhavi, Xiaolong Wang, Kiana Ehsani
Measuring the perception of the personalized activities with CloudIA robot
Alessandra Sorrentino, Laura Fiorini, Carlo La Viola, Filippo Cavallo
NetROS-5G: Enhancing Personalization through 5G Network Slicing and Edge Computing in Human-Robot Interactions
Anestis Dalgkitsis, Christos Verikoukis
The Impact of Robots' Facial Emotional Expressions on Light Physical Exercises
Nourhan Abdulazeem, Yue Hu
Autonomous and Adaptive Role Selection for Multi-robot Collaborative Area Search Based on Deep Reinforcement Learning
Lina Zhu, Jiyu Cheng, Hao Zhang, Zhichao Cui, Wei Zhang, Yuehu Liu
Building Ears for Robots: Machine Hearing in the Age of Autonomy
Xuan Zhong
What you need to know about a learning robot: Identifying the enabling architecture of complex systems
Helen Beierling, Phillip Richter, Mara Brandt, Lutz Terfloth, Carsten Schulte, Heiko Wersing, Anna-Lisa Vollmer
Robot Learning in the Era of Foundation Models: A Survey
Xuan Xiao, Jiahang Liu, Zhipeng Wang, Yanmin Zhou, Yong Qi, Qian Cheng, Bin He, Shuo Jiang