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
Multi-Robot Persistent Monitoring: Minimizing Latency and Number of Robots with Recharging Constraints
Ahmad Bilal Asghar, Shreyas Sundaram, Stephen L. Smith
Efficient Planning of Multi-Robot Collective Transport using Graph Reinforcement Learning with Higher Order Topological Abstraction
Steve Paul, Wenyuan Li, Brian Smyth, Yuzhou Chen, Yulia Gel, Souma Chowdhury
Can Large Language Models design a Robot?
Francesco Stella, Cosimo Della Santina, Josie Hughes
On the ethics of constructing conscious AI
Shimon Edelman
Forming and Controlling Hitches in Midair Using Aerial Robots
Diego S. D'Antonio, Subhrajit Bhattacharya, David Saldaña
Multimodal Reinforcement Learning for Robots Collaborating with Humans
Afagh Mehri Shervedani, Siyu Li, Natawut Monaikul, Bahareh Abbasi, Barbara Di Eugenio, Milos Zefran
Using a Variational Autoencoder to Learn Valid Search Spaces of Safely Monitored Autonomous Robots for Last-Mile Delivery
Peter J. Bentley, Soo Ling Lim, Paolo Arcaini, Fuyuki Ishikawa
RobotSweater: Scalable, Generalizable, and Customizable Machine-Knitted Tactile Skins for Robots
Zilin Si, Tianhong Catherine Yu, Katrene Morozov, James McCann, Wenzhen Yuan