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Intermittent Rendezvous Plans with Mixed Integer Linear Program for Large-Scale Multi-Robot Exploration

da Silva, Alysson Ribeiro, Chaimowicz, Luiz

arXiv.org Artificial Intelligence

Multi-Robot Exploration (MRE) systems with communication constraints have proven efficient in accomplishing a variety of tasks, including search-and-rescue, stealth, and military operations. While some works focus on opportunistic approaches for efficiency, others concentrate on pre-planned trajectories or scheduling for increased interpretability. However, scheduling usually requires knowledge of the environment beforehand, which prevents its deployment in several domains due to related uncertainties (e.g., underwater exploration). In our previous work, we proposed an intermittent communications framework for MRE under communication constraints that uses scheduled rendezvous events to mitigate such limitations. However, the system was unable to generate optimal plans and had no mechanisms to follow the plan considering realistic trajectories, which is not suited for real-world deployments. In this work, we further investigate the problem by formulating the Multi-Robot Exploration with Communication Constraints and Intermittent Connectivity (MRE-CCIC) problem. We propose a Mixed-Integer Linear Program (MILP) formulation to generate rendezvous plans and a policy to follow them based on the Rendezvous Tracking for Unknown Scenarios (RTUS) mechanism. The RTUS is a simple rule to allow robots to follow the assigned plan, considering unknown conditions. Finally, we evaluated our method in a large-scale environment configured in Gazebo simulations. The results suggest that our method can follow the plan promptly and accomplish the task efficiently. We provide an open-source implementation of both the MILP plan generator and the large-scale MRE-CCIC.


Communication-Constrained Multi-Robot Exploration with Intermittent Rendezvous

da Silva, Alysson Ribeiro, Chaimowicz, Luiz, Kumar, Vijay, Silva, Thales Costa, Hsieh, Ani

arXiv.org Artificial Intelligence

We propose a novel intermittent rendezvous method that allows robots to explore an unknown environment while sharing maps at rendezvous locations through agreements. In our method, robots update the agreements to spread the rendezvous locations during the exploration and prioritize exploring unknown areas near them. To generate the agreements automatically, we reduce the MRE to instances of the Job Shop Scheduling Problem (JSSP) and ensured intermittent communication through a temporal connectivity graph. We evaluate our method in simulation in various virtual urban environments and a Gazebo simulation using the Robot Operating System (ROS). Our results suggest Figure 1: Intermittent communication schematics of robots meeting at that our method can be better than using relays or maintaining rendezvous locations spread in a section of New York City. L1, L2, intermittent communication with a base station since we can and L3 are our hypothetical rendezvous locations, stars from the explore faster without additional hardware to create a relay same color are potential exploration zones near those locations, and network.