Demands to use washing robots in pig houses are growing up. The robot washes pig beds using a long arm over fences from passages. The passage is narrow so that the robot must detect the fences and run along the fences with high accuracy. A laser range scanner is useful to detect fences because there are many kinds of fences. However, the noises occur to the measured values if there are obstacles behind fences. In this study, the distance between scanned points and a path of robot is calculated and it is utilized with a zoned minimum filter to extract the points representing the fences. Then, the candidate lines are detected from the extracted points by Hough transform to detect multiple fences simultaneously. To run along the fences, the robot calculates the self-posture and distance to the detected fences. This paper describes the above proposed method and reports some experimental results of running along the fences and passing various intersections.

In this paper, we propose a novel approach to extracting rheological properties of deformable objects based on Haptic vision, which was proposed for vision-based automatic construction of virtual environment simulators. The method consists of two parts: 1) the "touch and see" part to cause deformation behavior by exerting known contact force on the object using a robot hand, and then observe how the deformed shape return to the original after contact force is removed, using a range sensor and a force-feedback sensor mounted on the robot hand, 2) the analysis and parameter extraction part from the acquired range images and force-feedback data. Experimental results using springs and wheat dough demonstrated the validity and effectiveness of the proposed approach to viscoelastic parameter extraction of rheological objects.

Real-world objects exhibit rich physical interaction behaviours on contact. Such behaviours depend on how heavy and hard it is when held, how its surface feels when touched, how it deforms on contact, etc. Recently, there are thus growing needs for haptic exploration to estimate and extract such physical object properties as mass, friction, elasticity, relational constraints etc.. In this paper, we propose a novel paradigm, we call haptic vision,which is a vision-based haptic exploration approach toward an automatic construction of reality-based virtual space simulator, by augmenting active vision with active touch. We apply this technique to mass, relational constraints estimation and elasticity, and use these results to construct virtual object manipulation simulator. Experimental results show that feasibility and validity of the proposed approach.