This article investigates the prerequisites for a global exploration strategy in an unknown environment on a virtual disaster site. Assume that a robot equipped with a laser range scanner can build a detailed map of a previous unknown environment. The remaining question is how to use this information on this map for further exploration. On a map several interesting locations can be present wher...

Striking the correct balance between global exploration of search spaces and local exploitation of promising basins of attraction is one of the principal concerns in the design of global optimization algorithms. This is true in the case of techniques based on global response surface approximation models as well. After constructing such a model using some initial database of designs it is far fr...

In this paper the preliminary design of multiple gravity-assist trajectories is formulated as a global optimization problem. An analysis of the structure of the solution space reveals a strong multimodality, which is strictly dependent on the complexity of the model. On the other hand it is shown how an oversimplification could prevent finding potentially interesting solutions. A trajectory mod...

Population diversity is crucial in evolutionary algorithms to enable global exploration and to avoid poor performance due to premature convergence. This book chapter reviews runtime analyses that have shown benefits of population diversity, either through explicit diversity mechanisms or through naturally emerging diversity. These works show that the benefits of diversity are manifold: diversit...

Nowadays, new lunar or planetary exploration missions including landers and rovers have been earnestly studied in Japan. Those missions will follow up a lunar global remote sensing mission Kaguya or a small body sample return mission Hayabusa. Space robotics technologies make a lot of important roles in order to achieve those missions. They will cover a pin-point landing technology, a reliable ...

The performance of off-policy learning, including deep Q-learning and deep deterministic policy gradient (DDPG), critically depends on the choice of the exploration policy. Existing exploration methods are mostly based on adding noise to the on-going actor policy and can only explore local regions close to what the actor policy dictates. In this work, we develop a simple meta-policy gradient al...

our civilization is based on metals, among other life supports. the existing ore deposits are becoming rapidly depleted by almost exponentially increasing demand and production and major new ore discoveries are needed. mineral exploration is supported by modern tools and scientific ideas, but geological characteristics of orebodies and their rock associations have still to be visualized.the tim...