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Feedback-based Information RoadMaps with Open Motion Planning Library
We are pleased to announce that the developers of OMPL (Open Motion Planning Library) at Rice University have posted a guest article by our lab on our latest work on integrating FIRM with OMPL. We would particularly like to acknowledge the support of Mark Moll in this process. Feel free to browse our code on […]
Bringing Belief Space Planning to Physical Systems
Sampling based deterministic motion planning has shown great success in the past. However, as we progress towards more realistic modeling and planning for robotic systems, we need to account for uncertainties in our systems. Uncertainties mainly arise from: 1. Sensing or measurement noise (also called observation noise) i.e. sensors do not give perfect measurements, instead […]
ICRA 2014, Hong Kong
Lab member Saurav Agarwal recently presented our group’s work on the application of FIRM to physical mobile robots (video above). FIRM (Feedback-based Information RoadMap) is a method developed by Dr. Ali-akbar Agha-mohammadi that allows for motion planning in belief space. We got to visit the Univ. of Hong Kong and see the ATLAS (Boston Dynamics) live in […]
Ali Agha joins LIDS@MIT for post-doc
Recently graduated lab member Dr. Ali-akbar Agha-mohammadi is now pursuing post-doctoral research at the Laboratory for Information and Decision Systems at MIT. You can visit his new page here.