The current results will facilitate the implementation of IAs in military settings and will provide useful data to the design of heterogeneous UxV teams.
For effective human-robot teaming, robots must gain the appropriate social-cognitive mechanisms that allow them to function naturally and intuitively in social interactions with humans. However, there is a lack of consensus on social cognition broadly, and how to design such mechanisms for embodied robotic systems. To this end, recommendations are advanced that are drawn from HRI, psychology, robotics, neuroscience and philosophy as well as theories of embodied cognition, dual process theory, ecological psychology, and dynamical systems. These interdisciplinary and multi-theoretic recommendations are meant to serve as integrative and foundational guidelines for the design of robots with effective social-cognitive mechanisms.
Abstract-We present AutonoVi:, a novel algorithm for autonomous vehicle navigation that supports dynamic maneuvers and satisfies traffic constraints and norms. Our approach is based on optimization-based maneuver planning that supports dynamic lane-changes, swerving, and braking in all traffic scenarios and guides the vehicle to its goal position. We take into account various traffic constraints, including collision avoidance with other vehicles, pedestrians, and cyclists using control velocity obstacles. We use a data-driven approach to model the vehicle dynamics for control and collision avoidance. Furthermore, our trajectory computation algorithm takes into account traffic rules and behaviors, such as stopping at intersections and stoplights, based on an arc-spline representation. We have evaluated our algorithm in a simulated environment and tested its interactive performance in urban and highway driving scenarios with tens of vehicles, pedestrians, and cyclists. These scenarios include jaywalking pedestrians, sudden stops from high speeds, safely passing cyclists, a vehicle suddenly swerving into the roadway, and high-density traffic where the vehicle must change lanes to progress more effectively.
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