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We describe a real-time model of terrain traversal by simulated human agents. Agent navigation includes a variety of simulated sensors, terrain reasoning with behavioral constraints, and detailed simulation of a variety of locomotion techniques. Our Kinematic Locomotion Generation Module (KLOG) generates various terrain navigation skills as well as both rhythmic and non-rhythmic variations of these skills. The terrain navigation skills include curved path walking, lateral or backward stepping, running, and the transitions between walking and running for motion continuity. Locomotion attributes such as pelvis rotation and translation and torso flexion and twist are used to modify the KLOG skills so that realistic looking rhythmic locomotion or non-rhythmic variations, such as ducking under a low hanging branch of a tree, can be achieved. The path through the terrain is incrementally computed by a behavioral reasoning system configuring a behavioral feedback network. A number of sensors acquire information on object range, passageways, obstacles, terrain type, exposure to hostile agents and so on. The behavioral reasoner weighs this information along with collision avoidance, cost, danger minimization, locomotion types and other behaviors available to the agent and incrementally attempts to reach a goal location. Since the system is reactive, it can respond to moving obstacles, changing terrain, or unexpected events due to hostile agents or the effects of limited perception.
Ko, H., Reich, B. D., Becket, W., & Badler, N. I. (1994). Terrain Navigation Skills and Reasoning. Retrieved from https://repository.upenn.edu/hms/107
Date Posted: 12 September 2007