Demo Videos

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Short introductory video of my PhD work: Finalist for AAAI-2015 Video Competition 

Short introductory video of my past research


For the publication corresponding to this video, please check here! You may also find a video of the approach extended to a dynamic environment with moving obstacle here.

-------------- Most recent videos/demos ---------------

IROS 2019 
Needle grasping optimisation in minimally invasive robotic surgery using haptic shared control

iros19video_final.mp4

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IROS, RA-L 2019 
A manipulability-driven path for end-effector trajectory constrained by Riemannian surface

iros2019v0.mp4




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 Humanoids2018 
Predictive grasping for collision-free manipulative movements 

IROS18_0152_VI_i.mp4


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Robotic and Autonomous Systems 
Robot from Demonstration: Emulation learning in environments with moving obstacles


main_ELS.mp4

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 IROS 2017     
Human-in-the-loop optimisation: Mixed-initiative grasping 

IROS2017_V04_060320170136.mp4

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 IROS 2017     
Safe robotic grasping

Nik_IROS2017.mp4

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 IROS 2017     

Analysis of the inertia and dynamics of grasped objects, for choosing optimal grasps to enable torque-efficient post-grasp manipulations

Humanoid2016.mp4


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 IROS 2016    

Task-relevant grasp selection: a joint solution to planning grasp and manipulative motion trajectories

IROS2016_Loughborough.mp4


 Finalist for AAAI-2015 Video Competition                    Robot Learning from Demonstration: From Mimicking to Emulation

AAAI_RLfD_Final.mp4


*** Submitted camera ready version of the video for inclusion in proceedings of the 2015 video competition.

ICRA 2015 Demo                        An Incremental Approach to Learning Generalizable Robot Tasks from Human Demonstration 

 

SWEEP-DEM-ICRA2015.mp4


s. 

 

AIII_331.mp4



Robot Learning from Demonstration: document




ICRA2015_final.mov




 



Robot Learning from Demonstration: a demo

 [2]: 
             

RLfD-I2E4-low.mp4


movie.mp4



TransPol2NewEnv.mp4


TransPolNewScenar.mp4


movie.mp4



       

    References:

  1.  A. M., Ghalamzan E.C. Paxton, G. D. Hager, L. Bascetta. “An incremental Approach to Learning Generalizable Robot Tasks from Human Demonstration” under preparation.
  2. A. M., Ghalamzan E.C. Paxton, G. D. Hager, L. Bascetta. “Learning How to Avoid an Obstacle from Demonstration” Robotic Science and Systems 2014, workshop on Learning Plans with Context from Human Signals. (PDF)


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