Behaviour based, autonomous and distributed scatter manoeuvres for satellite swarms

One of the key requirements of a satellite cluster is to maintain formation flight among its physically distinct elements while at the same time being capable of collision avoidance among each other and external threats. This paper addresses the capability of clusters with tens and scores of satellites to perform the collision avoidance manoeuvre in the event of an external, kinetic impact threat, via distributed autonomous control and to return to its original configuration after the threat has passed. Various strategies for response manoeuvres are proposed based on a path planning scheme called “equilibrium shaping”. The satellites in the cluster, modelled as a swarm of agents, follow biological rules of “avoidance” of each other and the threat, “gather” to maintain the formation cluster and “attraction” towards target location according to pre-defined artificial potential functions. The desired formation of this multi-agent system represents equilibrium points i.e., a minimum potential state, leading to predictable emergent behaviour for the entire cluster. The dynamical system is defined by adding a control feedback to the solution of the Hill–Clohessy–Wiltshire equations in order to track the desired velocities (as returned by the kinematic swarm model for equilibrium points). Various distributed path-planning, collision avoidance strategies are compared to each other in terms of the following metrics: delta-V spent during the manoeuvre, time required for the cluster to return to normal operations and distance of closest approach with the threat. Actuation and technological feasibility of the above strategies is benchmarked using available and potential CubeSAT system capabilities for propulsion, sensing and communication range. The significance of the results on designing future responsive, distributed space systems is discussed.

► We propose autonomous, distributed, behavior-based algorithms for a scatter manoeuvre. ► The algorithms are for satellite clusters of any size under external threat of kinetic impact. ► The satellites are modeled as a swarm of agents using artificial potential functions (APF). ► They follow the biological rules of avoidance, gather and attraction to calculate target states. ► Various strategies using APFs calculated by equilibrium shaping are compared to each other.