• Keyframe-based Learning from Demonstration Method and Evaluation 

      Akgun, Baris; Cakmak, Maya; Jiang, Karl; Thomaz, Andrea L. (Georgia Institute of TechnologySpringer, 2012-06)
      We present a framework for learning skills from novel types of demonstrations that have been shown to be desirable from a human-robot interaction perspective. Our approach –Keyframe-based Learning from Demonstration (KLfD)– ...
    • Robots learning actions and goals from everyday people 

      Akgun, Baris (Georgia Institute of Technology, 2015-11-16)
      Robots are destined to move beyond the caged factory floors towards domains where they will be interacting closely with humans. They will encounter highly varied environments, scenarios and user demands. As a result, ...
    • Sampling Heuristics for Optimal Motion Planning in High Dimensions 

      Akgun, Baris; Stilman, Mike (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2011-09)
      We present a sampling-based motion planner that improves the performance of the probabilistically optimal RRT* planning algorithm. Experiments demonstrate that our planner finds a fast initial path and decreases the ...
    • Trajectories and Keyframes for Kinesthetic Teaching: A Human-Robot Interaction Perspective 

      Akgun, Baris; Cakmak, Maya; Yoo, Jae Wook; Thomaz, Andrea L. (Georgia Institute of Technology, 2012-03)
      Kinesthetic teaching is an approach to providing demonstrations to a robot in Learning from Demonstration whereby a human physically guides a robot to perform a skill. In the common usage of kinesthetic teaching, the robot's ...