Expanding robot perception
MIT Associate Professor Luca Carlone works to give robots a more human-like perception of their environment, so they can interact with people safely and seamlessly.

Before you start
- Basic Python familiarity
- Comfort with algebra or calculus basics
- Interest in robotics systems
About this guide
MIT Associate Professor Luca Carlone works to give robots a more human-like perception of their environment, so they can interact with people safely and seamlessly.
Common questions
What will I learn in Expanding robot perception?
MIT Associate Professor Luca Carlone works to give robots a more human-like perception of their environment, so they can interact with people safely and seamlessly.
Is Expanding robot perception 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

Industrial Robotics
Image 3Preview this course # Industrial Robotics Mathematical models and practical applications Created byFabrizio Frigeni Last updated 9/2019 English Image 4Preview this course Purchase options Subscribe and save From$13.00/month Access to 28,000+ top-rated courses Cancel anytime

MIT xPRO | Robotics Essentials
MiT xPRO's Robotics Essentials program provides you with the knowledge and resources to identify basic robotic subsystems, evaluate human-robot interactions, and analyze challenges to the implementation of robotic systems. This program is an ideal launchpad if you want to chart a path in full-s

A neural blueprint for human-like intelligence in soft robots
A new AI control system enables soft robotic arms to learn a wide repertoire of motions and tasks once, then adjust to new scenarios on the fly without needing retraining or sacrificing functionality. The work was co-led by researchers at the Singapore-MIT Alliance for Research and Technology (SMART
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
[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
2.12: Introduction to Robotics | MIT Department of Mechanical Engineering
“This course is an introduction,” says instructor Professor Harry Asada. “We don’t assume anything about the students’ backgrounds. We just assume we share one thing in common: a love of complex motion. Motion is important in any area of mechanical engineering, but it’s particularly important in rob
Robots that use these skills

MAiRA
NEURA Robotics
MAiRA is a 7‑axis collaborative robot arm from NEURA Robotics designed for industrial automation with integrated AI perception and voice interaction.

AgiBot X1
AgiBot
AgiBot X1 is a 130 cm, 33 kg open-source humanoid platform with 34 DOF for research and education.

AiNex ROS Education AI Vision Humanoid Robot
Hiwonder
AiNex is a compact ROS-enabled educational humanoid robot from Hiwonder with an HD camera for AI vision experiments.
Refer a learner and get early access to our paid pathways and 1:1 mentorship pilot.
Join referral listNew robots, funding, and signals. Every Thursday.
Unsubscribe anytime.