This paper presents an evolutionary approach to solve the multi-objective min-max problem (MOMMP) that derives from the maximization of the Belief in robust design optimization. In evidence-based robust optimization, the solutions that minimize the design budgets are robust under epistemic uncertainty if they maximize the Belief in the realization of the value of the design budgets. Thus robust solutions are found by minimizing, with respect to the design variables, the global maximum with respect to the uncertain variables. This paper presents an algorithm to solve MOMMP, and a computational cost reduction technique based on Kriging metamodels. The results show that the algorithm is able to accurately approximate the Pareto front for a MOMMP at a fraction of the computational cost of an exact calculation.

This paper focuses on casting manipulation and presents an innovative mechanism that allows objects placed in a three-dimensional space to be reached with a relatively small robot. Casting manipulation is a technique by which a robotic end-effector is thrown and its ballistic flight is controlled through a tether cable so as to reach a target object. Previous work presented a solution that is viable only when the position of the target object is perfectly known or aligned with the throwing plane. Our work extends the technique by use of a novel mechanical design of the arm, and a suitable control scheme for the flight of the end-effector, which makes it applicable for objects placed at generic positions in a three-dimensional environment. Effectiveness of the casting robot was shown during the first ESA Lunar Robotics Challenge, where our team came in the second place.

This paper describes the design and implementation of DAVID, a lunar vehicle developed for the European Space Agency (ESA) Lunar Robotics Challenge, presenting severe terrain negotiation and sample acquisition challenges. We discuss in some detail two of the main innovative aspects of our entry to the challenge, i.e. the locomotion system and the sample acquisition system. Motivated by the challenge specifications, a range of different locomotion systems were considered, among which we chose a simple, rugged and effective wheeled system. We provide an account of the choice of five different types of wheels, which were designed, analyzed and experimentally tested in conditions similar to the challenge. The system eventually turned out to be very effective in negotiating 89% slopes of volcanic terrain on the challenge site, Mount Teide in Tenerife. To reduce the distance to be traveled on the difficult terrain and avoid risks in reaching the lowest parts of a crater, the vehicle was endowed with an innovative sample acquisition system, i.e. a casting manipulator. Casting manipulation is a technique in which the end-effector is thrown, the sample material is acquired, and the end-effector is retrieved using a light tether that acts as a "fishing line". The casting manipulator developed for DAVID uses an innovative sling-like technique, capable to obtain longer and more precise casts than previous oscillating versions. The analysis and experimental verification of DAVID's robot sling are reported, demonstrating its effectiveness. Finally, we give a brief account of the outcomes of the ESA Lunar Robotics Challenge, where our team came in second over other 8 teams that passed the final qualification phase.