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In this paper we present an approach to obstacle avoidance and local path planning for polygonal robots. It decomposes the task into a model stage and a planning stage. The model stage accounts for robot shape and dynamics using a reduced dynamic window. T ...
The exploration-exploitation trade-off that arises when one considers simple point estimates of expected returns no longer appears when full distributions are considered. This work develops a simple gradient-based approach for mainting such distributions a ...
Robot learning by imitation makes an increasing body of robotics research. Imitation learning complements motor learning techniques by restricting the search space to a computationally tractable subset. Imitation learning search for spatial and temporal in ...
This paper presents a new algorithm for classifying distributions. The algorithm combines the principle of margin maximization and a kernel trick, applied to distributions. Thus, it combines the discriminative power of support vector machines and the well- ...
Robotic ground vehicles are mechanisms that use gravity and contact forces with the ground to perform motion. They can either be wheeled, tracked or legged. In this thesis we will focus on n-wheeled vehicles able to perform ground following motion with all ...
It is important to establish reliable calculational tools to plan and analyse representative microdosimetry experiments in the context of microbeam radiation therapy development. In this paper, an attempt has been made to investigate the suitability of the ...
Australasian Coll. of Phys. Scientists and Engineers2003
The field of adaptive robotics involves simulations and real-world implementations of robots that adapt to their environments. In this article, I introduce adaptive environmentics -- the flip side of adaptive robotics -- in which the environment adapts to ...
We explore using particle swarm optimization on problems with noisy performance evaluation, focusing on unsupervised robotic learning. We adapt a technique of overcoming noise used in genetic algorithms for use with particle swarm optimization, and evaluat ...
We propose a semiparametric model for regression problems involving multiple response variables. The model makes use of a set of Gaussian processes that are linearly mixed to capture dependencies that may exist among the response variables. We propose an e ...
The simulation of mobility models such as the random waypoint often cause subtle problems, for example the decay of average speed as the simulation progresses, a difference between the long term distribution of nodes and the initial one, and sometimes the ...
