Virtual Elastic Tether: a New Approach for Multi-agent Navigation in Confined Aquatic Environments

Abstract

Underwater navigation is a challenging area in the field of mobile robotics due to inherent constraints in self-localisation and communication in underwater environments. Some of these challenges can be mitigated by using collaborative multi-agent teams. However, when applied underwater, the robustness of traditional multi-agent collaborative control approaches is highly limited due to the unavailability of reliable measurements. In this paper, the concept of a Virtual Elastic Tether (VET) is introduced in the context of incomplete state measurements, which represents an innovative approach to underwater navigation in confined spaces. The concept of VET is formulated and validated using the Cooperative Aquatic Vehicle Exploration System (CAVES), which is a sim-to-real multi-agent aquatic robotic platform. Within this framework, a vision-based Autonomous Underwater Vehicle-Autonomous Surface Vehicle leader-follower formulation is developed. Experiments were conducted in both simulation and on a physical platform, benchmarked against a traditional Image-Based Visual Servoing approach. Results indicate that the formation of the baseline approach fails under discrete disturbances, when induced distances between the robots exceeds 0.6 m in simulation and 0.3 m in the real world. In contrast, the VET-enhanced system recovers to pre-perturbation distances within 5 seconds. Furthermore, results illustrate the successful navigation of VET-enhanced CAVES in a confined water pond where the baseline approach fails to perform adequately.

Figures (14)

• Figure 1: Example of confined underwater space with low visibility, where environmental features such as walls are extremely hard to extract, complicating the application of traditional methods such as SLAM or feature-based odometry. Note that the picture was taken by an underwater motion capture camera with 5.3K resolution.
• Figure 2: Illustration of multiple cooperative aquatic robots. a) displays a robust connection between the AUV (green) and ASV (pink) was achieved by facilitating a physical tether between the robots; b) shows the AUV and ASV are using direct LoS camera views to formulate a virtual connection.
• Figure 3: Coordinate system of the proposed multi-agent platform.
• Figure 4: At time $k$, the left image shows three different effective areas in the image view, with the size of these areas adapting to the measurement of the actual tag size in the image frame, $\xi_k$ represents the tether state; the right image shows the tag dimensions in the image frame. Note that $l$ and $h$ are calculated based on the positions of the corners ($a$, $b$, $c$, and $d$) in the image frame. $V$ and $W$ are determined by the camera's pixels.
• Figure 5: Diagram of the proposed system. Sensor inputs and planner interface are identical between the simulation and physical platform. Feature points are provided by the Apriltag library Wang2016.