Jin-Woo Lee

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— We present a motion planner for autonomous highway driving that adapts the state lattice framework pioneered for planetary rover navigation to the structured environment of public roadways. The main contribution of this paper is a search space representation that allows the search algorithm to systematically and efficiently explore both spatial and(More)
For high-accuracy template-based-modeling of CASP7 targets, we have applied a procedure based on the rigorous optimization of score functions at three stages: multiple alignment, chain building, and side-chain modeling. We applied the conformational space annealing method to a newly developed consistency based score function for multiple alignment. For(More)
We have investigated the effect of rigorous optimization of the MODELLER energy function for possible improvement in protein all-atom chain-building. For this we applied the global optimization method called conformational space annealing (CSA) to the standard MODELLER procedure to achieve better energy optimization than what MODELLER provides. The method,(More)
A plausible consequence of the rugged folding energy landscapes inherent to biomolecules is that there may be more than one functionally competent folded state. Indeed, molecule-to-molecule variations in the folding dynamics of enzymes and ribozymes have recently been identified in single-molecule experiments, but without systematic quantification or an(More)
We present a new method for multiple sequence alignment (MSA), which we call MSACSA. The method is based on the direct application of a global optimization method called the conformational space annealing (CSA) to a consistency-based score function constructed from pairwise sequence alignments between constituting sequences. We applied MSACSA to two MSA(More)
— On-road motion planning for autonomous vehicles is in general a challenging problem. Past efforts have proposed solutions for urban and highway environments individually. We identify the key advantages/shortcomings of prior solutions, and propose a novel two-step motion planning system that addresses both urban and highway driving in a single framework.(More)
— This paper investigates real-time on-road motion planning algorithms for autonomous passenger vehicles (APV) in urban environments, and propose a computationally efficient planning formulation. Two key properties, tunability and stability , are emphasized when designing the proposed planner. The main contributions of this paper are: • A computationally(More)
This paper presents a cooperative decentralized path-planning algorithm for a group of autonomous agents that provides guaranteed collision-free trajectories in real-time. The algorithm is robust with respect to arbitrary delays in the wireless traffic, possible sources being transmission time and error correction. Agents move on reserved areas which are(More)