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
Before you start
- Basic Python familiarity
- Comfort with algebra or calculus basics
- Interest in robotics systems
About this guide
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 joint angles and cartesian frames. We'll do this in steps, the first step is to go from joint positions to cartesian frames: this is known as forward kinematics. [...] You might be tempted to think tha
Common questions
What will I learn in 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
Is Ch. 3 - Basic Pick and Place 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.
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.
Drake: Model-Based Design and Verification for Robotics
# Model-Based Design and Verification for Robotics A C++ / Python toolbox supported by the Toyota Research Institute. Install Learn More ## Core Library #### Modeling Dynamical Systems APITUTORIAL #### Solving Mathematical Programs APITUTORIAL #### Multibody Kinematics and Dynamics APITUTOR
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
Robotics | MIT News | Massachusetts Institute of Technology
Read full story → ### MIT engineers design an aerial microrobot that can fly as fast as a bumblebee With insect-like speed and agility, the tiny robot could someday aid in search-and-rescue missions. Read full story → ### New control system teaches soft robots the art of staying safe MIT CSAIL
Robots that use these skills
AUBO i10
AUBO Robotics
AUBO i10 is a 6-axis collaborative industrial robot arm with a 10 kg payload for factory automation.
LS20-B
Epson Robots
Epson Robots LS20-B is a 4-axis SCARA industrial robot designed for high-speed factory automation tasks up to 20 kg payload.
MZ07
Nachi-Fujikoshi
NACHI MZ07 is a compact 6-axis industrial articulated robot designed for high-speed handling and assembly tasks.
Refer a learner and get early access to our paid pathways and 1:1 mentorship pilot.
Join referral list