Abstract-Human environments possess a significant amount of underlying structure that is under-utilized in motion planning and mobile manipulation. In domestic environments for example, walls and shelves are static, large objects such as furniture and kitchen appliances most of the time do not move and do not change, and objects are typically placed on a limited number of support surfaces such as tables, countertops or shelves. Motion planning for robots operating in such environments should be able to exploit this structure to improve its performance with each execution of a task. In this paper, we develop an online motion planning approach which learns from its planning episodes (experiences) a graph, an Experience Graph. This graph represents the underlying connectivity of the space required for the execution of the mundane tasks performed by the robot. The planner uses the Experience graph to accelerate its planning efforts whenever possible and gracefully degenerates to planning from scratch if no previous planning experiences can be reused. On the theoretical side, we show that planning with Experience graphs is complete and provides bounds on suboptimality with respect to the graph that represents the original planning problem. On the experimental side, we show in simulations and on a physical robot that our approach is particularly suitable for higher-dimensional motion planning tasks such as planning for single-arm manipulation and two armed mobile manipulation. The approach provides significant speedups over planning from scratch and generates predictable motion plans: motions planned from start positions that are close to each other, to goal positions that are also close to each other, are similar. In addition, we show how the Experience graphs can incorporate solutions from other approaches such as human demonstrations, providing an easy way of bootstrapping motion planning for complex tasks.

Abstract-Many robotic systems are comprised of two or more arms. Such systems range from dual-arm household manipulators to factory floors populated with a multitude of industrial robotic arms. While the use of multiple arms increases the productivity of the system and extends dramatically its workspace, it also introduces a number of challenges. One such challenge is planning the motion of the arm(s) required to relocate an object from one location to another. This problem is challenging because it requires reasoning over which arms and in which order should manipulate the object, finding a sequence of valid handoff locations between the consecutive arms and finally choosing the grasps that allow for successful handoffs. In this paper, we show how to exploit the characteristics of this problem in order to construct a planner that can solve it effectively. We analyze our approach experimentally on a number of simulated examples ranging from a 2-arm system operating at a table to a 3-arm system working at a bar and to a 4-arm system in a factory setting.

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Of all the many changes of the world economy since World War II, few have been nearly so dramatic as the resurrection of global finance. A review of five recent books suggests considerable diversity of opinion concerning both the causes and the consequences of financial globalization, leaving much room for further research. Competing historical interpretations, stressing the contrasting roles of market forces and government policies, need to be reexamined for dynamic linkages among the variables they identify. Likewise, impacts on state policy at both the macro and micro levels should be explored more systematically to understand not just whether constraints may be imposed on governments but also how and under what conditions, and what policymakers can do about them. Finally, questions are also raised about implications for the underlying paradigm conventionally used for the study of international political economy and international relations more generally.

A common currency, as envisioned in the Maastricht treaty, is thought to be the surest way to "lock in" commitments to monetary cooperation among sovereign states. But historical evidence suggests otherwise. Comparative analysis of six currency unions demonstrates that while economic and organizational factors are influential in determining the sustainability of monetary cooperation, interstate politics matters most. Compliance with commitments is greatest in the presence of either a locally dominant state, willing and able to use its influence to sustain monetary cooperation, or a broad network of institutional linkages sufficient to make the loss of monetary autonomy tolerable to each partner. Copyright 1993 Blackwell Publishers Ltd..