On the use of redundant manipulator techniques for control of platoons of cooperating robotic vehicles

Flocking for Multi-Robot Systems via the Null-Space-based Behavioral Control

“…A possible technique to handle the tasks' composition has been proposed by [8] and [9], which consists of assigning a relative priority to the single task functions by resorting to the task-priority inverse kinematics introduced by [13] and [17] for ground-fixed redundant manipulators. Nevertheless, as discussed by [12], just in the case of conflicting tasks it is necessary to devise singularity-robust algorithms that ensure proper functioning of the inverse velocity mapping.…”

Formation Control of Underactuated Surface Vessels using the Null-Space-Based Behavioral Control

“…For each task, a function that measures its degree of fulfilment (e.g., a cost or a potential function) can be defined; thus, in a static environment, the task is achieved when its output is constant at a value that minimizes the task function. Following the techniques inherited from inverse kinematics for industrial manipulators described in [11], [12], the NSB uses a hierarchybased logic to combine multiple conflicting tasks. In particular, the NSB is able to fulfill or partially fulfill each task according to their position in the hierarchy and according to the eventual conflicts with the highest-priority tasks.…”

Competitive Evolution of Tactical Multiswarm Dynamics

“…How complex systems develop from undirected local relationships is often obscure and is the focus of swarm intelligence research. Identifying the emergent properties and behaviors of a swarm, given individual agent-operating parameters, can be difficult without simulation or implementation [3], [9], and training agents to accomplish a given task grows in complexity with larger groups due to the plurality of interactions. Hand-tuning the operating scheme of a complex system to perform over a prolonged period of time can generate unintended and counterintuitive emergent behaviors, and largescale deterministic plans may fail if the operational theater is perturbed.…”

“…Swarm inversion is an improvement algorithm that is meant to refine the solution toward an improved but not necessarily optimal solution. Emergent behavior is an aspect of swarm intelligence and refers to large groups of agents interacting under simple rules that exhibit some added cooperative benefit and has applications in communications [1], [5], [11], robotics [2], [3], [6], and optimization [4], [13], [14], [20]. Swarms often demonstrate robustness, plasticity, and decentralization [4], which are ideal characteristics for modeling autonomous large-group interactions.…”