I will present several state-of-the-art annotation systems and their relationship with dense correspondences. I will try to compare them with my own work now.
Reference papers:
LabelMe video: Building a Video Database with Human Annotations (ICCV 2009)
link
Efficiently Scaling up Crowdsourced Video Annotation (IJCV 2013)
link
Human-Assisted Motion Annotation (CVPR 2008)
link
Annotation Propagation in Large Image Databases via Dense Image Correspondence (ECCV 2012)
link
Tuesday, April 15, 2014
Wednesday, April 09, 2014
Lab meeting April 10, 2014 (Channing): "CAPT: Concurrent assignment and planning of trajectories for multiple robots"
Title: CAPT: Concurrent assignment and planning of trajectories for multiple robots
Authors: Matthew Turpin, Nathan Michael, and Vijay Kumar
GRASP Laboratory, University of Pennsylvania, Philadelphia, USA
In: The International Journal of Robotics Research (IJRR), January 2014, 33: 98-112
Abstract:
In this paper, we consider the problem of concurrent assignment and planning of trajectories (which we denote CAPT) for a team of robots. This problem involves simultaneously addressing two challenges: (1) the combinatorially complex problem of finding a suitable assignment of robots to goal locations, and (2) the generation of collision-free, time parameterized trajectories for every robot. We consider the CAPT problem for unlabeled (interchangeable) robots and propose algorithmic solutions to two variations of the CAPT problem. The first algorithm, C-CAPT, is a provably correct, complete, centralized algorithm which guarantees collision-free optimal solutions to the CAPT problem in an obstacle-free environment. To achieve these strong claims, C-CAPT exploits the synergy obtained by combining the two subproblems of assignment and trajectory generation to provide computationally tractable solutions for large numbers of robots. We then propose a decentralized solution to the CAPT problem through d-CAPT, a decentralized algorithm that provides suboptimal results compared to C-CAPT . We illustrate the algorithms and resulting performance through simulation and experimentation.
Authors: Matthew Turpin, Nathan Michael, and Vijay Kumar
GRASP Laboratory, University of Pennsylvania, Philadelphia, USA
In: The International Journal of Robotics Research (IJRR), January 2014, 33: 98-112
Abstract:
In this paper, we consider the problem of concurrent assignment and planning of trajectories (which we denote CAPT) for a team of robots. This problem involves simultaneously addressing two challenges: (1) the combinatorially complex problem of finding a suitable assignment of robots to goal locations, and (2) the generation of collision-free, time parameterized trajectories for every robot. We consider the CAPT problem for unlabeled (interchangeable) robots and propose algorithmic solutions to two variations of the CAPT problem. The first algorithm, C-CAPT, is a provably correct, complete, centralized algorithm which guarantees collision-free optimal solutions to the CAPT problem in an obstacle-free environment. To achieve these strong claims, C-CAPT exploits the synergy obtained by combining the two subproblems of assignment and trajectory generation to provide computationally tractable solutions for large numbers of robots. We then propose a decentralized solution to the CAPT problem through d-CAPT, a decentralized algorithm that provides suboptimal results compared to C-CAPT . We illustrate the algorithms and resulting performance through simulation and experimentation.
Download link: http://ijr.sagepub.com/content/33/1/98.full.pdf
Related Media link: http://www.seas.upenn.edu/~mturpin/summary.html
Subscribe to:
Posts (Atom)