Learning Guide — MIT OpenCourseWare

Robotic Manipulation

- Pseudo-inverse as an optimization - Adding velocity constraints - Adding position and acceleration constraints - Joint centering - Tracking a desired pose - Alternative formulations + Exercises Chapter 4: Geometric Pose Estimation + Cameras and depth sensors - Depth sensors - Simulation + Re

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Prerequisites

Before you start

  • Basic Python familiarity
  • Comfort with algebra or calculus basics
  • Interest in robotics systems
Course Detail

About this guide

  • Pseudo-inverse as an optimization
  • Adding velocity constraints
  • Adding position and acceleration constraints
  • Joint centering
  • Tracking a desired pose
  • Alternative formulations
  • Exercises

Chapter 4: Geometric Pose Estimation

  • Cameras and depth sensors
  • Depth sensors
  • Simulation
  • Representations for geometry
  • Point cloud registration with known correspondences
  • Iterative Closest Point (ICP)
  • Dealing with partial views and outliers [...] and the idea that birds with articulate
Frequently Asked

Common questions

What will I learn in Robotic Manipulation?

- Pseudo-inverse as an optimization - Adding velocity constraints - Adding position and acceleration constraints - Joint centering - Tracking a desired pose - Alternative formulations + Exercises Chapter 4: Geometric Pose Estimation + Cameras and depth sensors - Depth sensors - S

Is Robotic Manipulation 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.

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