Adaptive Tuning of Multi-Robot Systems for The Effective Mapping and Tracking of Dynamic Environments

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Multi-robot systems (MRS) are about to positively disrupt and boost several key economic sectors, while also offering unique solutions to some of the grand challenges faced by humanity, such as dealing with climate change and increasing agricultural productivity. However, even the state-of-the-art in MRS technology suffers from a slow pace of collective response compared to what would be required to autonomously operate in real-world dynamic settings. The proposed Discovery research program will address this critical issue by exploiting the unique advantages of novel ultra-responsive collective behaviors exhibited by robot swarms when confronted with changing circumstances. The long-term aim of the proposed research is to design, develop and demonstrate innovative ultra-responsive collective behaviors of MRS operating in large-scale, unstructured, and fast-evolving environments. The research program will focus on four short-term objectives: (1) Leverage heterogeneous swarming for highly responsive collective mapping and tracking; (2) Optimally balance exploration and exploitation by means of adaptive collective decision-making; (3) Infer new swift collective maneuvers through multi-agent adversarial inverse reinforcement learning; (4) Develop a class of benchmark problems to quantify the effectiveness of MRS operations in highly dynamic environments. The scientific approaches consist of a blend of theory, multi-agent simulations, and MRS experiments appropriate to meet our objectives, and essential if real advances toward our long-term aim are to be made. The work will be partitioned between two doctoral and two master theses, providing opportunities for HQP to participate in exciting, cutting-edge research of high societal impact with direct benefit for Canada's high-tech industry. Several international collaborations (U.S., France, Singapore, The Netherlands) will amplify and augment the achievements of this program. The proposed Discovery research program with its innovations on ultra-responsive collective dynamics of MRS is expected to have a significant impact on applications in field robotics, agricultural and industrial robotics. Ultimately, the success of this program has the potential to be a catalyst in the fast-emerging market of multi-robot automation, which is experiencing a dramatic surge owing to a very high demand by several key sectors of Canada's economy. The innovations arising from this research program can give a fresh impetus to the pivotal transformation of Canada's agricultural sector toward ultra-precision and autonomous farming. To leverage the full potential of robotics and automation towards Agriculture 5.0, more fundamental research at low technological readiness levels is required. This is precisely what this Discovery research program is about, specifically novel advances and innovative solutions for the ultra-rapid coordination of heterogeneous systems, with learning and adaptation.