Synergies in Feature Localization by Air-Ground Robot Teams

Abstract

Abstract. This paper describes the implementation of a decentralized architecture for autonomous teams of aerial and ground vehicles engaged in active perception. We provide a theoretical framework based on an established approach to the underlying sensor fusion problem [3]. This provides transparent integration of information from heterogeneous sources. The approach is extended to include an information-theoretic utility measure that captures the task objective and robot inter-dependencies. A distributed solution mechanism is employed to determine information maximizing trajectories and assignments subject to the constraints of individual vehicle and sensor sub-systems. This architecture enables the benefit of the complementary aerial and ground based vehicle and sensor capabilities to be realized. The approach is applied to missions involving searching for and tracking multiple ground targets. Experimental results for vehicles equipped with cameras are presented. These illustrate the impact of the team configuration on overall system performance.

Control for Localization of Targets using Range-only Sensors

“…Grocholsky et al (2004) used the mutual information gain of a particular control action as a metric to determine the desirability of that action. Maximizing this metric at each step resulted in rapid shrinking of the estimation uncertainty.…”

Cooperative air and ground surveillance

“…While many details were omitted because of space constraints, the details of the hardware and software integration are presented in [10] and [12]. The methods described here lend themselves to decentralized control of heterogeneous vehicles without requiring any tailoring to the specific capabilities of the vehicles or their sensors.…”

“…In [9], we developed control algorithms that refine the quality of estimates, addressing both the detection and the localization problems. Our approach to active sensing and localization with UAVs and UGVs, briefly summarized in this article, is discussed in greater detail in [10]. Our work on scalable coordinated coverage with UAVs is also discussed in a previous paper [11].…”

Cooperative Control for Localization of Mobile Sensor Networks

“…However, before our proposed scheme can be scaled to larger teams, we must consider how these algorithms can be distributed between robots so each robot can develop local estimates of state and independently make decisions on how to move to improve its estimates. The decentralized architecture for fusing sensory information and the coordinated control strategy for air-ground coordination proposed in [21] offer a starting point in this direction.…”