Lecture

Attention-based Robot Learning of Haptic Interaction

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Description

This lecture by the instructor focuses on haptic attention modeling for robot learning, where a novel architecture is presented to integrate tactile measurements over time. The robot autonomously executes haptic glances to identify object classes, achieving a high performance rate. The architecture adapts its exploration policy based on acquired data, leading to robust object class estimation. Real-world validation of the control scheme is discussed, along with enhancing haptic interaction efficiency by extending the parametrization of haptic glances.

Official source

Related concepts (10)

Cognitive robotics

Cognitive Robotics or Cognitive Technology is a subfield of robotics concerned with endowing a robot with intelligent behavior by providing it with a processing architecture that will allow it to learn and reason about how to behave in response to complex goals in a complex world. Cognitive robotics may be considered the engineering branch of embodied cognitive science and embodied embedded cognition, consisting of Robotic Process Automation, Artificial Intelligence, Machine Learning, Deep Learning, Optical Character Recognition, , Process Mining, Analytics, Software Development and System Integration.

Nao (robot)

Nao (pronounced now) is an autonomous, programmable humanoid robot formerly developed by Aldebaran Robotics, a French robotics company headquartered in Paris, which was acquired by SoftBank Group in 2015 and rebranded as SoftBank Robotics. The robot's development began with the launch of Project Nao in 2004. On 15 August 2007, Nao replaced Sony's robot dog Aibo as the robot used in the RoboCup Standard Platform League (SPL), an international robot soccer competition.

Robotics

Robotics is an interdisciplinary branch of electronics and communication, computer science and engineering. Robotics involves the design, construction, operation, and use of robots. The goal of robotics is to design machines that can help and assist humans. Robotics integrates fields of mechanical engineering, electrical engineering, information engineering, mechatronics engineering, electronics, biomedical engineering, computer engineering, control systems engineering, software engineering, mathematics, etc.

Human–robot interaction

Human–robot interaction (HRI) is the study of interactions between humans and robots. Human–robot interaction is a multidisciplinary field with contributions from human–computer interaction, artificial intelligence, robotics, natural language processing, design, and psychology. A subfield known as physical human–robot interaction (pHRI) has tended to focus on device design to enable people to safely interact with robotic systems. Human–robot interaction has been a topic of both science fiction and academic speculation even before any robots existed.

Mobile robot

A mobile robot is an automatic machine that is capable of locomotion. Mobile robotics is usually considered to be a subfield of robotics and information engineering. Mobile robots have the capability to move around in their environment and are not fixed to one physical location. Mobile robots can be "autonomous" (AMR - autonomous mobile robot) which means they are capable of navigating an uncontrolled environment without the need for physical or electro-mechanical guidance devices.

Related lectures (33)

Robot Learning and Control

Covers learning and adaptive control for robots, focusing on real-time reactivity and path planning using dynamical systems.

Robots: Safe Collaboration

Covers challenges and solutions for robots to work safely with humans, emphasizing adaptability and predictability.

Acquiring Data for Learning

Explores training robots through reinforcement learning and learning from demonstration, highlighting challenges in human-robot interaction and data collection.

Bayesian Disturbance Injection: Robust Imitation

Explores Bayesian disturbance injection for robust imitation in robot learning, demonstrating its effectiveness in reducing error compounding and achieving high task achievement.

Rethinking robot learning for autonomy at scale