Information-Based Task-Level Planning

这个研究启动奖是理论和 机器人零件装配的实验工作。 理论 研究将确定简单的信息不变量 操作任务：固有的装配时间权衡 感知、行动和预测。 埃德曼博士将测试他的 理论上的机器人零件定向系统，与传感和 操作任务沿着信息不变分解 边界 这项研究可能会改善制造业 设计以及可靠和高效的部件装配。

This Research Initiation Award is for theoretical and experimental work in robotic parts assembly. The theoretical research will identify information invariants for simple manipulation tasks: inherent assembly-time tradeoffs between sensing, action, and prediction. Dr. Erdmann will then test his theory on a robotic parts-orienting system, with sensing and manipulatory tasks decomposed along information-invariant boundaries. This research could lead to improved manufacturing design as well as reliable and efficient parts assembly.