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The undergraduates who worked in the lab last summer will be presenting two posters at the ASME IMECE conference based on their summer work. If you’re attending IMECE in Pittsburgh, please stop by on November 11!

Brendan Bogar will present “Investigating a Framework for Visualizing Reinforcement Learning Algorithms via Quadrupedal Robotic Simulation”.

David Chan, Mel Nguyen, Oshadha Gunasekara, and Randall Kliman will present “An object-oriented framework for fast development and testing of mobile robot control algorithms”. Abstracts are available on the IMECE website.

I will be heading to Madrid in October to present at the Human/Robot-in-the-Loop Machine Learning workshop at IROS 2018. The workshop is on Monday October 1. Hope to see you there!

Welcome Brendan Bogar to the lab! He will be spending the summer working with us as part of the University of Arizona Undergraduate Research Opportunities Consortium – Summer Research Institute (UROC-SRI) program.

Brendan will be working on building simulations of quadrupedal legged locomotion. This will build on earlier work by Cameron Zawacki, some of which can be seen here.

I am on my way to ICRA 2018 to present our work on multirobot foraging using multiarmed bandits. We will be participating in the Monday workshop on Informative Path Planning and Adaptive Sampling. Hope to see you there!

Now that the spring semester is over, we are quickly transitioning to summer research mode. This week, we have welcomed four students:

David Chan, University of Arizona, Electrical and Computer Engineering

Mel Nguyen, University of Arizona, Electrical and Computer Engineering

Oshadha Gunasekara, Carnegie Mellon University, Electrical and Computer Engineering and Robotics

Randall Kliman, Georgia Tech, Computer Engineering.

They are working on lab infrastructure, integrating our motion capture system and a fleet mobile robots using ROS. More updates as the summer, and the work, progresses!

The below two videos show, respectively, the physical state and the full state space of a motivation dynamics agent. The agent is motivated to visit each of the two goal states (red diamonds) while staying in the workspace (the black circle) and avoiding the obstacles (black discs with red circles at their centers).

The motivation dynamics are as described in our SIADS paper. As guaranteed by the analysis in the paper, the closed-loop system exhibits a stable limit cycle where the agent cyclically visits each of the goal states in turn.

Our paper “A dynamical system for prioritizing and coordinating motivations” has been accepted for publication in the SIAM Journal on Applied Dynamical Systems. The arXiv preprint has been updated accordingly.