A faster way to teach a robot
A new technique enables a human to efficiently fine-tune a robot that failed to complete a desired task with very little effort on the part of the human. Their system uses algorithms, counterfactual explanations, and feedback from the user to generate synthetic data it uses to quickly fine-tune the

Before you start
- Basic Python familiarity
- Comfort with algebra or calculus basics
- Interest in robotics systems
About this guide
A new technique enables a human to efficiently fine-tune a robot that failed to complete a desired task with very little effort on the part of the human. Their system uses algorithms, counterfactual explanations, and feedback from the user to generate synthetic data it uses to quickly fine-tune the robot.
Common questions
What will I learn in A faster way to teach a robot?
A new technique enables a human to efficiently fine-tune a robot that failed to complete a desired task with very little effort on the part of the human. Their system uses algorithms, counterfactual explanations, and feedback from the user to generate synthetic data it uses to qu
Is A faster way to teach a robot free?
HumanoidHub has not verified public pricing for this guide. Open MIT OpenCourseWare for the current access terms before enrolling.
Do I need any prerequisites?
Recommended prep: Basic Python familiarity; Comfort with algebra or calculus basics; Interest in robotics systems.
How long does it take?
Self-paced (provider defined). Most learners complete this guide in self-directed sessions over a few weeks.
Does it offer a certificate?
This guide does not include a formal certificate. Focus is on the learning material itself.
Related guides
A new model offers robots precise pick-and-place solutions
SimPLE (Simulation to Pick Localize and placE), a new model developed by MIT researchers, learns to pick, regrasp and place objects using object’s computer-aided design (CAD) model

Helping robots practice skills independently to adapt to unfamiliar environments
A robot rapidly specializes its skills using parameter policy learning, where the machine can rapidly specialize at specific, smaller actions within a long-horizon task. The MIT CSAIL algorithm enables autonomous practice to improve at mobile-manipulation activities.

Lecture 8.4: Stefanie Tellex - Human-Robot Collaboration | MIT Learn
<p><strong>Description: Human collaboration with robots that perform actions in real-world environments, carry out complex sequences of actions and actively coordinate with people, establishing a social-feedback loop. <p><strong>Instructor: Stefanie Tellex

Open-source platform simulates wildlife for soft robotics designers - MIT Schwarzman College of Computing
Since the term “soft robotics” was adopted in 2008, engineers in the field have been building diverse representations of flexible machines useful in exploration, locomotion, rehabilitation, and even space. One source of inspiration: the way animals move in the wild. A team of MIT researchers has tak

Unit 8. Robotics | Brains, Minds and Machines Summer Course | Brain and Cognitive Sciences
This page summarizes the unit topic and activities, and links to lecture videos, notes and further study resources.
[PDF] Humanoid Robots as Cooperative Partners for People
guide the search by providing timely feedback, luring the learner to perform desired behaviors, controlling the environment so the appropriate cues are easy to attend to, etc. Our architecture supports the construction of collaborative learners that are easy and rewarding to teach using techniques t
Robots that use these skills

ANYmal X
ANYbotics
ANYmal X is an ATEX/IECEx-certified quadruped inspection robot from ANYbotics for operation in explosive industrial zones.

Sanbot Elf
Qihan Technology
Sanbot Elf is a compact wheeled service robot from Qihan Technology for reception, guidance, and interactive engagement.
1X EVE
1X Technologies
1X EVE is a wheeled humanoid robot from 1X Technologies aimed at mobile service work in institutional and industrial settings.
Refer a learner and get early access to our paid pathways and 1:1 mentorship pilot.
Join referral list