Multiple target interception

1. A method comprising:

operating a swarm of autonomous vehicles to maximize a number of intercepted targets, wherein, for each of said autonomous vehicles, the method comprises:

identifying a plurality of objects in an operational area as targets or obstacles;

for each of said plurality of objects, determining a probability density function (PDF) location parameter, representing probability density of location, and geometry;

calculating a trajectory of motion for said autonomous vehicle based on said location parameters of each of said plurality of objects, wherein said calculating: (i) maximizes a probability of intercepting each of said targets by said autonomous vehicle, and (ii) applies a predefined bound on a probability of avoiding collisions with each of said obstacles; and

moving said autonomous vehicle along said trajectory of motion,

wherein said calculating is performed by each of said autonomous vehicles separately of all other said autonomous vehicles in said swarm of autonomous vehicles.

2. The method of claim 1 , wherein said identifying comprises determining a distance between said autonomous vehicle and at least some of said plurality of objects.

3. The method of claim 2 , wherein said calculating is based, at least in part, on said determined distances.

4. The method of claim 1 , wherein said operating comprises repeating iteratively said identifying, determining, calculating, and moving, until all said targets are intercepted.

5. The method of claim 1 , wherein said location parameter of an object comprises a geographical location of said object.

6. The method of claim 1 , wherein at least some of said identifying and said determining comprises receiving information from an external source selected from a group consisting of: a sensing unit of said autonomous vehicle, another autonomous vehicle, and a control center.

7. The method of claim 1 , wherein said calculating comprises weighting said probability of intercepting and said probability of avoiding collisions based, at least in part, on a count of said plurality of objects.

8. The method of claim 1 , wherein the obstacles comprise at least one other autonomous vehicle of the swarm of autonomous vehicles.

9. The method of claim 1 , wherein, with respect to a target, said intercepting comprises at least one of: achieving physical proximity to the target, destroying the target, monitoring the target, and changing the target.

10. A swarm of autonomous vehicles, each comprising at least one hardware processor, and a non-transitory computer-readable storage medium having stored thereon program instructions, the program instructions executable by the at least one hardware processor to operate said autonomous vehicle to:

identify a plurality of objects in an operational area as targets or obstacles;

determine a probability density function (PDF) location parameter, representing probability density of location and geometry for each of said plurality of objects;

calculate a trajectory of motion for said autonomous vehicle, based, at least in part, on said location parameters of each of said plurality of objects, wherein said calculating: (i) maximizes a probability of intercepting each of said targets by said autonomous vehicle, and (ii) applies a predefined bound on a probability of avoiding collisions with each of said obstacles; and

move said autonomous vehicle along said trajectory of motion,

wherein said calculating is performed by each of said autonomous vehicles separately of all other said autonomous vehicles in said swarm of autonomous vehicles.

11. The swarm of claim 10 , wherein said identifying comprises determining a distance between said autonomous vehicle and at least some of said plurality of objects.

12. The swarm of claim 11 , wherein said calculating is based, at least in part, on said determined distances.

13. The swarm of claim 10 , wherein said operating comprises repeating iteratively said identifying, determining, calculating, and moving, until all said targets are intercepted.

14. The swarm of claim 10 , wherein said location parameter of an object comprises a geographical location of said object.

15. The swarm of claim 10 , wherein at least some of said identifying and said determining comprises receiving information from an external source selected from the group consisting of: a sensing unit of said autonomous vehicle, another autonomous vehicle, and a control center.

16. The swarm of claim 10 , wherein said calculating comprises weighting said probability of intercepting and said probability of avoiding collisions based, at least in part, on a count of said plurality of objects.

17. The swarm of claim 10 , wherein the obstacles comprise at least one other autonomous vehicle of the swarm of autonomous vehicles.

18. The swarm of claim 10 , wherein, with respect to a target, said intercepting comprises at least one of: achieving physical proximity to the target, destroying the target, monitoring the target, and changing the target.