Robohub.org
 

Social learning

by
29 August 2010



share this:

Robots are portrayed as tomorrows helpers, be it in schools, hospitals, workplaces or homes. Unfortunately, such robots won’t be truly useful out-of-the-box because of the complexity of real-world environments and tasks. Instead, they will need to learn how to interact with objects in their environment to produce a desired outcome (affordance learning).

For this purpose, robots can explore the world while using machine learning techniques to update their knowledge. However, the learning process is sometimes saturated with examples of objects, actions and effects that won’t help the robot in its purpose.

In these cases, humans or other social partners can help direct robot learning (social learning). Most studies have focussed on scenarios where a teacher demonstrates how to correctly do a task. The robot then imitates the teacher by reproducing the same actions to achieve the same goals.

This approach, while being very efficient, typically means that the teacher needs to take time to train the robot, which can be burdensome. Furthermore, the robot might be so specialized for the demonstrated scenario that it will have trouble performing tasks that slightly differ. In addition, imitation only works when the teacher and robot have similar motion constraints and morphologies.

Luckily, humans and animals use a large variety of mechanisms to learn from social partners. Tapping into this reservoir, Cakmak et al. propose mechanisms where:
– robots interact with the same objects as the social partner (stimulus enhancement)
– robots try to achieve the same effect on the same object as the social partner (emulation)
– robots reproduce the same action as the social partner (mimicking)

Experiments performed in simulation compare stimulus enhancement, emulation, mimicking, imitation and non-social learning in a large variety of situations. The results summarize which mechanisms are better suited for which scenarios in a series of very useful guidelines. Demonstrations with two robots, Jimmy and Jane, were done to validate the study. Don’t miss the excellent video below for a summary of the article.

In the future, Cakmak et al. will focus on combining learning approaches to harness the full potential of this rich set of mechanisms.



tags:


Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory
Sabine Hauert is President of Robohub and Associate Professor at the Bristol Robotics Laboratory





Related posts :



Robotics Today latest talks – Raia Hadsell (DeepMind), Koushil Sreenath (UC Berkeley) and Antonio Bicchi (Istituto Italiano di Tecnologia)

Robotics Today held three more online talks since we published the one from Amanda Prorok (Learning to Communicate in Multi-Agent Systems). In this post we bring you the last talks that Robotics Today (currently on hiatus) uploaded to their YouTube channel: Raia Hadsell from DeepMind talking about ‘Scalable Robot Learning in Rich Environments’, Koushil Sreenath from UC Berkeley talking about ‘Safety-Critical Control for Dynamic Robots’, and Antonio Bicchi from the Istituto Italiano di Tecnologia talking about ‘Planning and Learning Interaction with Variable Impedance’.
21 October 2021, by and

Sense Think Act Pocast: Erik Schluntz

In this episode, Audrow Nash interviews Erik Schluntz, co-founder and CTO of Cobalt Robotics, which makes a security guard robot. Erik speaks about how their robot handles elevators, how they have hum...
19 October 2021, by and

A robot that finds lost items

Researchers at MIT have created RFusion, a robotic arm with a camera and radio frequency (RF) antenna attached to its gripper, that fuses signals from the antenna with visual input from the camera to locate and retrieve an item, even if the item is buried under a pile and completely out of view.
18 October 2021, by

Robohub gets a fresh look

If you visited Robohub this week, you may have spotted a big change: how this blog looks now! On Tuesday (coinciding with Ada Lovelace Day and our ‘50 women in robotics that you need to know about‘ by chance), Robohub got a massive modernisation on its look by our technical director Ioannis K. Erripis and his team.
17 October 2021, by
ep.

339

podcast

High Capacity Ride Sharing, with Alex Wallar

In this episode, our interviewer Lilly speaks to Alex Wallar, co-founder and CTO of The Routing Company. Wallar shares his background in multi-robot path-planning and optimization, and his research on scheduling and routing algorithms for high-capacity ride-sharing. They discuss how The Routing Company helps cities meet the needs of their people, the technical ins and outs of their dispatcher and assignment system, and the importance of public transit to cities and their economics.
12 October 2021, by

50 women in robotics you need to know about 2021

It’s Ada Lovelace Day and once again we’re delighted to introduce you to “50 women in robotics you need to know about”! From the Afghanistan Girls Robotics Team to K.G.Engelhardt who in 1989 ...
12 October 2021, by and





©2021 - ROBOTS Association


 












©2021 - ROBOTS Association