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
A Review of Scene Representations for Robot Manipulators
Carter Sifferman
Co-evolving morphology and control of soft robots using a single genome
Fabio Tanaka, Claus Aranha
Scalable Multi-Agent Reinforcement Learning for Warehouse Logistics with Robotic and Human Co-Workers
Aleksandar Krnjaic, Raul D. Steleac, Jonathan D. Thomas, Georgios Papoudakis, Lukas Schäfer, Andrew Wing Keung To, Kuan-Ho Lao, Murat Cubuktepe, Matthew Haley, Peter Börsting, Stefano V. Albrecht
Stochastic Nonlinear Ensemble Modeling and Control for Robot Team Environmental Monitoring
Victoria Edwards, Thales C. Silva, M. Ani Hsieh
Influence of collaborative customer service by service robots and clerks in bakery stores
Yuki Okafuji, Sichao Song, Jun Baba, Yuichiro Yoshikawa, Hiroshi Ishiguro
Evaluating Multimodal Interaction of Robots Assisting Older Adults
Afagh Mehri Shervedani, Ki-Hwan Oh, Bahareh Abbasi, Natawut Monaikul, Zhanibek Rysbek, Barbara Di Eugenio, Milos Zefran