10,232 research outputs found
Robust grasping under object pose uncertainty
This paper presents a decision-theoretic approach to problems that require accurate placement of a robot relative to an object of known shape, such as grasping for assembly or tool use. The decision process is applied to a robot hand with tactile sensors, to localize the object on a table and ultimately achieve a target placement by selecting among a parameterized set of grasping and information-gathering trajectories. The process is demonstrated in simulation and on a
real robot. This work has been previously presented in Hsiao et al. (Workshop on Algorithmic Foundations of Robotics (WAFR), 2008; Robotics Science and Systems (RSS), 2010) and Hsiao (Relatively robust grasping, Ph.D. thesis, Massachusetts Institute of Technology, 2009).National Science Foundation (U.S.) (Grant 0712012
Motion Planning for Unlabeled Discs with Optimality Guarantees
We study the problem of path planning for unlabeled (indistinguishable)
unit-disc robots in a planar environment cluttered with polygonal obstacles. We
introduce an algorithm which minimizes the total path length, i.e., the sum of
lengths of the individual paths. Our algorithm is guaranteed to find a solution
if one exists, or report that none exists otherwise. It runs in time
, where is the number of robots and is the total
complexity of the workspace. Moreover, the total length of the returned
solution is at most , where OPT is the optimal solution cost. To
the best of our knowledge this is the first algorithm for the problem that has
such guarantees. The algorithm has been implemented in an exact manner and we
present experimental results that attest to its efficiency
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