For bipedal robots walking on uneven terrain, lack of information about a terrain may cause serious reduction of the stability. To solve the problem, the purpose of this paper is to develop a sensor which can be mounted on robot's soles and propose methods which can increase the stability of bipedal walk with the sensor. The sensor should detect information including relative posture and relative distance between the sole of the swing leg and the floor, when the robot execute the walk by ZMP-based control. In this paper, the sensor has been designed based on Net-Structure Proximity Sensor (NSPS) and a prototype has been developed. The developed sensor is with thin structure, light weight, less wirings (four wires only) and fast response (<1[ms]). Experimental results show that the sensor can output necessary relative posture and positon between the sole and the floor for walk control. Besides, the sensor has been mounted to the soles of a hobby robot and its feasibility is shown by controlling robot so that its sole can land on a tilted floor with maximum contacting area to improve the stability.
This paper proposes a multimodal interactive approach to improving recognition performance of objects a person indicates to a robot. We considered two phenomena in human-human and human-robot interaction to design the approach: alignment and alignment inhibition. Alignment is a phenomenon that people tend to use the same words or gestures as their interlocutor uses; alignment inhibition is an opposite phenomenon, which people tend to decrease the amount of information in their words and gestures when their interlocutor uses excess information. Based on the phenomena, we designed robotic behavior policies that a robot should use enough information without being excessive to identify objects so that people would use similar information with the robot to refer to those objects, which would contribute to improve recognition performance. To verify our design, we developed a robotic system to recognize the objects to which people referred and conducted an experiment in which we manipulated the redundancy of information used in the confirmation behavior. The results showed that proposed approach improved recognition performance of objects to which referred by people.