Human-like Planning for Reaching in Cluttered Environments
Mohamed Hasan,Matthew Warburton,Wisdom C. Agboh,Mehmet R. Dogar,Matteo Leonetti,He Wang,Faisal Mushtaq,Mark Mon-Williams,Anthony G. Cohn,Mohamed Hasan,Matthew Warburton,Wisdom C. Agboh,Mehmet R. Dogar,Matteo Leonetti,He Wang,Faisal Mushtaq,Mark Mon-Williams,Anthony G. Cohn
Humans, in comparison to robots, are remarkably adept at reaching for objects in cluttered environments. The best existing robot planners are based on random sampling of configuration space- which becomes excessively high-dimensional with large number of objects. Consequently, most planners often fail to efficiently find object manipulation plans in such environments. We addressed this problem by ...
