SIAM Snowbird

With the end of the semester fast approaching, we’re getting close to conference season! My student Craig Thompson and I will be speaking at SIAM’s Dynamical Systems conference in Snowbird next month. Hope to see you there!

Students presenting at IMECE

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.

Welcome summer students!

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!

    Motivation dynamics simulations

    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.