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
Efficient automatic design of robots
David Matthews, Andrew Spielberg, Daniela Rus, Sam Kriegman, Josh Bongard
Situational Adaptive Motion Prediction for Firefighting Squads in Indoor Search and Rescue
Nils Mandischer, Frederik Schicks, Burkhard Corves
Music Mode: Transforming Robot Movement into Music Increases Likability and Perceived Intelligence
Catie Cuan, Emre Fisher, Allison Okamura, Tom Engbersen
Internet of Things Meets Robotics: A Survey of Cloud-based Robots
Chrisantus Eze