Multi-robot Target Tracking Research Articles

Cooperative Target Tracking in Aquatic Environment Using Dual Robotic Dolphins

This article proposes a modified rapidly exploring random tree (RRT)-based path planner and behavior-based cooperative tracking strategy for a dual robotic dolphin system to fulfill a cooperative target-tracking task. Specifically, with full consideration of both task requirements and mechatronic configuration, a robotic dolphin with a waist-caudal propulsive mechanism for thrust forces and differential bilateral flippers for maneuverability is developed. To satisfy the demand of fast path planning, a variant RRT algorithm is employed to generate feasible paths for the dual robotic dolphins with fewer waypoints, faster convergence speed, and better stability. Furthermore, a behavior-based approach in conjunction with centralized architecture is implemented to achieve high-level decision-making. Finally, simulations, analysis, as well as field experiments are carried out to verify the effectiveness of the proposed control scheme. The success of the experiments further offers insight into the mechanisms of cooperative multirobot target tracking in aquatic environments.

An integrated particle filter and potential field method applied to cooperative multi-robot target tracking

We describe a novel method whereby a particle filter is used to create a potential field for robot control without prior clustering. We show an application of this technique to control a team of mobile robots to cooperatively locate and track a moving target. The particle filter models a probability distribution over the estimated location of the target, providing robust tracking despite frequent target occlusion. This method extends previous work in particle-filter-based tracking in two important ways. First, the particle cloud is never clustered to find a single estimate of target location. Instead, robot motion is guided by a potential field generated directly from the particle cloud. Secondly, effective coordinated multi-robot searching and tracking can be achieved by simply assigning a subset of the particles to each robot. Simulation trials and real robot experiments demonstrate the method successfully locating and tracking targets, and experiments show that multiple coordinated robots outperform a similar but uncoordinated team.