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.

Before you start
- Basic Python familiarity
- Comfort with algebra or calculus basics
- Interest in robotics systems
About this guide
This page summarizes the unit topic and activities, and links to lecture videos, notes and further study resources.
Common questions
What will I learn in 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.
Is Unit 8. Robotics | Brains, Minds and Machines Summer Course | Brain and Cognitive Sciences free?
Yes — this guide is free to access through MIT OpenCourseWare. Some providers may offer paid certificates separately.
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
[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
[PDF] Humanoid Robots: A New Kind of Tool - People | MIT CSAIL
to the environment? How can the system adapt to changing conditions and learn new tasks? Each humanoid robotics lab must address many of the same motor-control, perception, and machine-learning problems. [...] Learning through imitation. Humans acquire new skills and new goals through imitation. Imi
Ch. 3 - Basic Pick and Place
# Forward kinematics The spatial algebra gets us pretty close to what we need for our pick and place algorithm. But remember that the interface we have with the robot reports measured joint positions, and expects commands in the form of joint positions. So our remaining task is to convert between j
Robots that use these skills

NEURA 4NE1
NEURA Robotics
NEURA 4NE1 is a full-size humanoid robot platform from NEURA Robotics aimed at industrial and logistics tasks, with NVIDIA Thor compute and a reservation-based rollout.
1X EVE
1X Technologies
1X EVE is a wheeled humanoid robot from 1X Technologies aimed at mobile service work in institutional and industrial settings.

AGIBOT A2
AgiBot
AGIBOT A2 is a bipedal humanoid robot platform for R&D and education, with onboard compute, vision sensors, and autonomous navigation.
Refer a learner and get early access to our paid pathways and 1:1 mentorship pilot.
Join referral list