Heuristics and Rescheduling in Prioritised Multi-Robot Path Planning: A Literature Review

The benefits of multi-robot systems are substantial, bringing gains in efficiency, quality, and cost, and they are useful in a wide range of environments from warehouse automation, to agriculture and even extend in part to entertainment. In multi-robot system research, the main focus is on ensuring efficient coordination in the operation of the robots, both in task allocation and navigation. However, much of this research seldom strays from the theoretical bounds; there are many reasons for this, with the most prominent and -impactful being resource limitations. This is especially true for research in areas such as multi-robot path planning (MRPP) and navigation coordination. This is a large issue in practice as many approaches are not designed with meaningful real-world implications in mind and are not scalable to large multi-robot systems. This survey aimed to look into the coordination and path-planning issues and challenges faced when working with multi-robot systems, especially those using a prioritised planning approach and identify key areas that are not well-explored and the scope of applying existing MRPP approaches to real-world settings

Human-Aware Motion Planning for Safe Human-Robot Collaboration

With the rapid adoption of robotic systems in our daily lives, robots must operate in the presence of humans in ways that improve safety and productivity. Currently, in industrial settings, human safety is ensured through physically separating the robotic system from the human. However, this greatly decreases the set of shared human-robot tasks that can be accomplished and also reduces human-robot team fluency. In recent years, robots with improved sensing capabilities have been introduced and the feasibility of humans and robots co-existing in shared spaces has become a topic of interest. This thesis proposes a human-aware motion planning approach building on RRT-Connect, dubbed Human-Aware RRT-Connect, that plans in the presence of humans. The planner considers a composite cost function that includes human separation distance and visibility costs to ensure the robot maintains a safety distance during motion while being as visible as possible to the human. A danger criterion cost considering two mutually dependent factors, human-robot center of mass distance and robot inertia, is also introduced into the cost formulation to ensure human safety during planning. A simulation study is conducted to demonstrate the planner performance. For the simulation study, the proposed Human-Aware RRT-Connect planner is evaluated against RRT-Connect through a set of problem scenarios that vary in environment and task complexity. Several human-robot configurations are tested in a shared workspace involving a simulated Franka Emika Panda arm and human model. Through the problem scenarios, it is shown that the Human-Aware RRT-Connect planner, paired with the developed HRI costs, performs better than the baseline RRT-Connect planner with respect to a set of quantitative metrics. The paths generated by the Human-Aware RRT-Connect planner maintain larger separation distances from the human, are more visible and also safer due to the minimization of the danger criterion. It is also shown that the proposed HRI cost formulation outperforms formulations from previous work when tested with the Human-Aware RRT-Connect planner

Making the Case for Human-Aware Navigation in Warehouses

This work addresses the performance of several local planners for navigation of autonomous pallet trucks in the presence of humans in a simulated warehouse as well as a complementary approach developed within the ILIAD project. Our focus is to stress the open problem of a safe manoeuvrability of pallet trucks in the presence of moving humans. We propose a variation of ROS navigation stack that includes in the planning process a model of the human robot interaction