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In order for robots and other artificial agents to efficiently learn to perform useful tasks defined by an end user, they must understand not only the goals of those tasks, but also the structure and dynamics of that user's environment.…

人工智能 · 计算机科学 2019-07-22 Robert Loftin , Bei Peng , Matthew E. Taylor , Michael L. Littman , David L. Roberts

The common consensus is that robots designed to work alongside or serve humans must adhere to the ethical standards of their operational environment. To achieve this, several methods based on established ethical theories have been…

人工智能 · 计算机科学 2024-07-24 Rajitha Ramanayake , Vivek Nallur

For robots to navigate and interact more richly with the world around them, they will likely require a deeper understanding of the world in which they operate. In robotics and related research fields, the study of understanding is often…

For intelligent robots to interact in meaningful ways with their environment, they must understand both the geometric and semantic properties of the scene surrounding them. The majority of research to date has addressed these mapping…

机器人学 · 计算机科学 2017-08-04 Niko Sünderhauf , Trung T. Pham , Yasir Latif , Michael Milford , Ian Reid

A major challenge to deploying robots widely is navigation in human-populated environments, commonly referred to as social robot navigation. While the field of social navigation has advanced tremendously in recent years, the fair evaluation…

High-level robot skills represent an increasingly popular paradigm in robot programming. However, configuring the skills' parameters for a specific task remains a manual and time-consuming endeavor. Existing approaches for learning or…

机器人学 · 计算机科学 2024-08-23 Claudius Kienle , Benjamin Alt , Onur Celik , Philipp Becker , Darko Katic , Rainer Jäkel , Gerhard Neumann

With the recent advances in machine learning, creating agents that behave realistically in simulated air combat has become a growing field of interest. This survey explores the application of machine learning techniques for modeling air…

机器学习 · 计算机科学 2025-10-08 Patrick Ribu Gorton , Andreas Strand , Karsten Brathen

Dynamic task allocation is an essential requirement for multi-robot systems operating in unknown dynamic environments. It allows robots to change their behavior in response to environmental changes or actions of other robots in order to…

机器人学 · 计算机科学 2007-05-23 Kristina Lerman , Chris Jones , Aram Galstyan , Maja J Mataric

Robot learning provides a number of ways to teach robots simple skills, such as grasping. However, these skills are usually trained in open, clutter-free environments, and therefore would likely cause undesirable collisions in more complex,…

机器人学 · 计算机科学 2022-12-13 Vitalis Vosylius , Edward Johns

Personalization is critical for the advancement of service robots. Robots need to develop tailored understandings of the environments they are put in. Moreover, they need to be aware of changes in the environment to facilitate long-term…

机器人学 · 计算机科学 2025-06-18 Akash Chikhalikar , Ankit A. Ravankar , Jose Victorio Salazar Luces , Yasuhisa Hirata

In this paper, we present a comprehensive analysis and discussion of energy consumption in agricultural robots. Robots are emerging as a promising solution to address food production and agroecological challenges, offering potential…

机器人学 · 计算机科学 2024-10-11 Alexis Bras , Alix Montanaro , Cyrille Pierre , Marilys Pradel , Johann Laconte

We describe an algorithm for motion planning based on expert demonstrations of a skill. In order to teach robots to perform complex object manipulation tasks that can generalize robustly to new environments, we must (1) learn a…

机器人学 · 计算机科学 2016-02-16 Chris Paxton , Marin Kobilarov , Gregory D. Hager

This work proposes a novel multi-robot task allocation framework for robots that can switch between multiple modes, e.g., flying, driving, or walking. We first provide a method to encode the multi-mode property of robots as a graph, where…

机器人学 · 计算机科学 2025-03-18 Takumi Ito , Riku Funada , Mitsuji Sampei , Gennaro Notomista

Most of the grand challenges of humanity today involve complex agent-based systems, such as epidemiology, economics or ecology. However, remains as a pending task the challenge of identifying the general principles underlying their…

综合金融 · 定量金融 2020-10-19 Martin Jaraiz

It is intractable for assistive robots to have all functionalities pre-programmed prior to deployment. Rather, it is more realistic for robots to perform supplemental, on-site learning about user's needs and preferences, and particularities…

机器人学 · 计算机科学 2022-10-19 Nina Moorman , Erin Hedlund-Botti , Matthew Gombolay

The market for domestic robots made to perform household chores is growing as these robots relieve people of everyday responsibilities. Domestic robots are generally welcomed for their role in easing human labor, in contrast to industrial…

机器人学 · 计算机科学 2024-05-30 Arpita Soni , Sujatha Alla , Suresh Dodda , Hemanth Volikatla

The information available to robots in real tasks is widely distributed both in time and space, requiring the agent to search for relevant data. In humans, that face the same problem when sounds, images and smells are presented to their…

机器人学 · 计算机科学 2013-07-23 Esther L. Colombini , Alexandre S. Simões , Carlos H. C. Ribeiro

This paper formally defines a robot system, including its sensing and actuation components, as a general, topological dynamical system. The focus is on determining general conditions under which various environments in which the robot can…

机器人学 · 计算机科学 2024-02-29 Vadim K. Weinstein , Steven M. LaValle

Tidying up a household environment using a mobile manipulator poses various challenges in robotics, such as adaptation to large real-world environmental variations, and safe and robust deployment in the presence of humans.The Partner Robot…

To act in the world, robots rely on a representation of salient task aspects: for example, to carry a coffee mug, a robot may consider movement efficiency or mug orientation in its behavior. However, if we want robots to act for and with…

机器人学 · 计算机科学 2024-01-30 Andreea Bobu , Andi Peng , Pulkit Agrawal , Julie Shah , Anca D. Dragan