Controls for Assistive Robots
Guangzheng Zang
EECS Department, University of California, Berkeley
Technical Report No. UCB/EECS-2017-79
May 12, 2017
http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-79.pdf
The industry of robotics is on the rise; an increasing number of robots are being used in factories and households. Our capstone project – Controls for Assistive Robots – deals with this market demand. We aim to implement and integrate various subsystems of UC Berkeley’s InterACT lab to enhance its infrastructure. My technical contribution is a robot perception system that gives the robot the ability to “see” and interact with the environment. Specifically, we implemented a vision system using Microsoft’s Kinect v2 sensor. We managed to make the Kinect a quantitative sensor ready to use in research. We also integrated it with other subsystems in the lab and build a system so that the robot could detect the pose of certain objects in real world, and plan to grab them in a 3D virtual environment. With the systems we developed, future researchers in the lab will be able to conduct their own research and keep making a meaningful impact to the robotics industry.
BibTeX citation:
@mastersthesis{Zang:EECS-2017-79, Author= {Zang, Guangzheng}, Title= {Controls for Assistive Robots}, School= {EECS Department, University of California, Berkeley}, Year= {2017}, Month= {May}, Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-79.html}, Number= {UCB/EECS-2017-79}, Abstract= {The industry of robotics is on the rise; an increasing number of robots are being used in factories and households. Our capstone project – Controls for Assistive Robots – deals with this market demand. We aim to implement and integrate various subsystems of UC Berkeley’s InterACT lab to enhance its infrastructure. My technical contribution is a robot perception system that gives the robot the ability to “see” and interact with the environment. Specifically, we implemented a vision system using Microsoft’s Kinect v2 sensor. We managed to make the Kinect a quantitative sensor ready to use in research. We also integrated it with other subsystems in the lab and build a system so that the robot could detect the pose of certain objects in real world, and plan to grab them in a 3D virtual environment. With the systems we developed, future researchers in the lab will be able to conduct their own research and keep making a meaningful impact to the robotics industry.}, }
EndNote citation:
%0 Thesis %A Zang, Guangzheng %T Controls for Assistive Robots %I EECS Department, University of California, Berkeley %D 2017 %8 May 12 %@ UCB/EECS-2017-79 %U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-79.html %F Zang:EECS-2017-79