From Dynamic Programming to RRTs: Algorithmic Design of Feasible Trajectories
نویسنده
چکیده
This paper summarizes our recent development of algorithms that construct feasible trajectories for problems that involve both differential constraints (typically in the form of an underactuated nonlinear system), and global constraints (typically arising from robot collisions). Dynamic programming approaches are described that produce approximately-optimal solutions for low-dimensional problems. Rapidly-exploring Random Tree (RRT) approaches are described that can find feasible, non-optimal solutions for higher-dimensional problems. Several key issues for future research are discussed.
منابع مشابه
LQR-Based Heuristics for Rapidly Exploring State Space
Kinodynamic planning algorithms like RapidlyExploring Randomized Trees (RRTs) hold the promise of finding feasible trajectories for rich dynamical systems with complex, non-convex constraints. In practice, these algorithms perform very well on configuration space planning, but struggle to grow efficiently in systems with dynamics or differential constraints when using conventional proximity met...
متن کاملBiomechanical Investigation of Empirical Optimal Trajectories Introduced for Snatch Weightlifting
The optimal barbell trajectory for snatch weightlifting has been achieved empirically by several researchers. They have studied the differences between the elite weightlifters’ movement patterns and suggested three optimal barbell trajectories (type A, B, and C). But they didn’t agree for introducing the best trajectory. One of the reasons is this idea that the selected criterion by researchers...
متن کاملOpen pit limit optimization using dijkstra’s algorithm
In open-pit mine planning, the design of the most profitable ultimate pit limit is a prerequisite to developing a feasible mining sequence. Currently, the design of an ultimate pit is achieved through a computer program in most mining companies. The extraction of minerals in open mining methods needs a lot of capital investment, which may take several decades. Before the extraction, the p...
متن کاملA dynamic programming approach for solving nonlinear knapsack problems
Nonlinear Knapsack Problems (NKP) are the alternative formulation for the multiple-choice knapsack problems. A powerful approach for solving NKP is dynamic programming which may obtain the global op-timal solution even in the case of discrete solution space for these problems. Despite the power of this solu-tion approach, it computationally performs very slowly when the solution space of the pr...
متن کاملA Quadratic Regulator - Based Heuristic for Rapidly Exploring State Space by Elena
Kinodynamic planning algorithms like Rapidly-Exploring Randomized Trees (RRTs) hold the promise of finding feasible trajectories for rich dynamical systems with complex, non-convex constraints. In practice, these algorithms perform very well on configuration space planning, but struggle to grow efficiently in systems with dynamics or differential constraints. This is due in part to the fact tha...
متن کامل