This video demonstrates a mixed reality (MR) environment which is constructed for development of autonomous behaviors of robots. Many kinds of functions are required to be integrated for realizing an autonomous behavior. For example, autonomous navigation of humanoid robots needs functions, such as, recognition of environment, localization and mapping, path planning, gait planning, dynamically stable biped walking pattern generation, and sensor feedback stabilization of walking. Technologies to realize each function are well investigated by many research works. However, another effort is required for constructing an autonomous behavior by integrating those functions. We demonstrate a MR environment in which internal status of a robot, such as, sensor status, recognition results, planning results, and motion control parameters, can be projected to the environment and its body. We can understand intuitively how each function works as a part of total system in the real environment by using the proposed system, and it helps solving the integration problems. The overview of the system, projection of each internal status, and the application to an autonomous locomotion experiment are presented in the video clip.

One of the problems in developing a humanoid robot is caused by the fact that intermediate results, such as what the robot perceives the environment, and how it plans its moving path are hard to be observed online in the physical environment. What developers can see is only the behavior. Therefore, they usually investigate logged data afterwards, to analyze how well each component worked, or which component was wrong in the total system. In this paper, we present a novel environment for robot development, in which intermediate results of the system are overlaid on physical space using mixed reality technology. Real-time observation enables the developers to see intuitively, in what situation the specific intermediate results are generated, and to understand how results of a component affected the total system. This feature makes the development efficient and precise. This environment also gives a human-robot interface that shows the robot internal state intuitively, not only in development, but also in operation.

Efficient placement and routing algorithms are presented for the modules of a bipolar analog LSI. In the layout of an analog module, a grid-free technique is required to minimize the module area and geometric constraint observance is necessary for the circuit performance optimization. The placement algorithm determines cell positions observing the geometric constraints by vertex-grouping of the constraint graph representing the relative device positions in the input circuit diagram. The routing algorithm, based on the characteristic fine-grid maze router, allows grid-free routing and variable width routings observing the geometric constraints by dynamically generating wiring prohibition. These algorithms are applied to the design of the analog modules. Automatically designed modules are compact and the performance requirements are met.>