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
On the Disentanglement of Tube Inequalities in Concentric Tube Continuum Robots
Reinhard M. Grassmann, Anastasiia Senyk, Jessica Burgner-Kahrs
Learning Input Constrained Control Barrier Functions for Guaranteed Safety of Car-Like Robots
Sven Brüggemann, Dominic Nightingale, Jack Silberman, Maurício de Oliveira
Talk Through It: End User Directed Manipulation Learning
Carl Winge, Adam Imdieke, Bahaa Aldeeb, Dongyeop Kang, Karthik Desingh
Decentralized Lifelong Path Planning for Multiple Ackerman Car-Like Robots
Teng Guo, Jingjin Yu
A System for Human-Robot Teaming through End-User Programming and Shared Autonomy
Michael Hagenow, Emmanuel Senft, Robert Radwin, Michael Gleicher, Michael Zinn, Bilge Mutlu
Software Engineering for Robotics: Future Research Directions; Report from the 2023 Workshop on Software Engineering for Robotics
Claire Le Goues, Sebastian Elbaum, David Anthony, Z. Berkay Celik, Mauricio Castillo-Effen, Nikolaus Correll, Pooyan Jamshidi, Morgan Quigley, Trenton Tabor, Qi Zhu