This paper considers a new, complex problem of UAV/UGV collaborative efforts to search and capture attackers under uncertainty. The goal of the defenders (UAV/UGV team) is to stop all attackers as quickly as possible, before they arrive at their selected goal. The uncertainty considered is twofold: the defenders do not know the attackers' location and destination, and there is also uncertainty in the defenders' sensing. We suggest a real-time algorithmic framework for the defenders, combining entropy and stochastic-temporal belief, that aims at optimizing the probability of a quick and successful capture of all of the attackers. We have empirically evaluated the algorithmic framework, and have shown its efficiency and significant performance improvement compared to other solutions.

This paper describes the design and development of a robot with six soft limbs, with the dual capability of pushing-based locomotion and grasping by wrapping around objects. Specifically, a central platform lodges six silicone limbs, radially distributed, with cables embedded. A new mechanism-specific gait, invariant regarding the number of limbs, has been implemented. Functionally, some limbs provide stability while others push and pull the robot to locomote in the desired direction. Once the robot is close to a target, one limb is elected to wrap around the object and, thanks to the particular limb structure and the soft material, a friction-based grasping is achieved. The robot is inspired by the octopus and implements the key principles of locomotion in this animal, without coping the full body structure. For this reason it works in water, but it is not restricted to this environment. The experiments show the effectiveness of the original solution in locomotion and grasping.