— Modeling robot motion planning with uncertainty in a Bayesian framework leads to a computationally intractable stochastic control problem. We seek hypotheses that can justify a...
Andrea Censi, Daniele Calisi, Alessandro De Luca, ...
In this paper, we propose a long-term motion model for visual object tracking. In crowded street scenes, persistent occlusions are a frequent challenge for tracking algorithm and ...
Haifeng Gong, Jack Sim, Maxim Likhachev, Jianbo Sh...
Autonomous robots use sensors to perceive and track objects in the world. Tracking algorithms use object motion models to estimate the position of a moving object. Tracking effic...
We present a fast goal-directed motion synthesis technique that integrates sample-based planning methods with constraint-based dynamics simulation using a finite element formulati...
In this paper, we consider the problem of motion planning for mobile robots with nonlinear hybrid dynamics, and high-level temporal goals. We use a multi-layered synergistic framew...