Robohub.org
 

Todd Murphey: Active Learning in Robot Motion Control | CMU RI Seminar


by
27 April 2019



share this:

Link to video on YouTube

Abstract: “Motion motivated by information needs can be found throughout natural systems, yet there is comparatively little work in robotics on analyzing and synthesizing motion for information. Instead, engineering analysis of robots and animal motion typically depends on defining objectives and rewards in terms of states and errors on states. This is how we formulate optimal control objectives, learning-based reward functions, and goals for sample-based planning. Sometimes coverage algorithms are used to manage the collection of data, distributing sensors across a domain, but often without explicitly reasoning about where useful information is likely to be present. This talk will focus on situations where motion is used for information, either obtaining information or communicating information. Ergodicity provides one means for relating a trajectory to information content, and I will talk about settings both in animal behavior and in physical Human-Robot Interaction where movement appears to be ergodic. These information-based analysis tools can also be used to synthesize motion, connecting control decisions to learning needs—a form of active learning. Examples from biology, vision-based tracking, and contact-based sensing will serve as examples throughout the talk.”




John Payne





Related posts :



Women in robotics you need to know about 2025

  06 Oct 2025
This global list celebrates women's impact across the robotics ecosystem and globe.

Robot Talk Episode 127 – Robots exploring other planets, with Frances Zhu

  03 Oct 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Frances Zhu from the Colorado School of Mines about intelligent robotic systems for space exploration.

Rethinking how robots move: Light and AI drive precise motion in soft robotic arm

  01 Oct 2025
Researchers at Rice University have developed a soft robotic arm capable of performing complex tasks.

RoboCup Logistics League: an interview with Alexander Ferrein, Till Hofmann and Wataru Uemura

and   25 Sep 2025
Find out more about the RoboCup league focused on production logistics and the planning.

Drones and Droids: a co-operative strategy game

  22 Sep 2025
Scottish Association for Marine Science is running a crowdfunding campaign for educational card game.

Call for AAAI educational AI videos

  22 Sep 2025
Submit your contributions by 30 November 2025.

Self-supervised learning for soccer ball detection and beyond: interview with winners of the RoboCup 2025 best paper award

  19 Sep 2025
Method for improving ball detection can also be applied in other fields, such as precision farming.



 

Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


 












©2025.05 - Association for the Understanding of Artificial Intelligence