In order to enable disaster rescue and information collection for disaster aid, we have been working to develop collaborative field robot system with multi-rotor extended robots. In this paper, we propose new multi-rotor flying robots that have special functions beyond flying ability. The robot is named MUWA: Multi-field Universal Wheel for Air-land Vehicle with Quad Variable-pitch Propellers. MUWA is variable pitch quad-rotors flying robot for multi-field locomotion, that is, standing and rolling at a given tilt angle on the ground like a tire, along with floating and moving on the water surface. The robot's purpose for action, structural design, basic control, and experiment of multi-field verification are covered.
In Fukushima Daiichi nuclear power plant in which the accident occurred by the East Japan Earthquake in 2011, in order to avoid radioactive exposure of workers, many robots are used. However, it seems that the nuclear peculiarity and the singularity of Fukushima obstruct ordinary robot technicians' entry. In order to make these barriers low, we explain how the nuclear power plant company is designing the robot, and argue also about the difficulty of mechatronics.
As of today, several rovers have been deployed on planetary surfaces and provided astonishing scientific achievements. A significant challenge in future missions is accurate localization for long distances to expand the activity range. After the successful Mars Exploration Rovers mission, visual odometry is regarded as a promising technique to provide accurate pose estimates on planetary surfaces. However, it should address the problem of terrain dependency since it cannot estimate motion in the terrain where visual features are lacked. This paper proposes a visual odometry system for untextured natural terrain which is devoid of features. Several key techniques are presented including a scheme for terrain-adaptive feature detection, and a motion estimation method using fewer feature points. The feasibility of the proposed techniques is supported by the field tests in a volcanic field using a test-bed rover.
Although the demand to build a dexterous robot like a human, i.e., a robot that can execute a given task robustly against the variation of the environment, is increasing, it is difficult to implement an explicit sensory feedback law to adapt the variation of the environment. To solve the above problem, transferring human skills to robots has attracted attention in the robotics community and direct teaching is known as one of the powerful methods to transfer human skills to robots. We have already proposed a method to extract human skill automatically by using direct teaching. In this method, human skill is extracted in two aspects, i.e., appropriate nominal trajectories and sensory feedback laws. However, the proposed method didn't consider the direction of correlation between the force and the velocity and is limited to a specific DOF system with a specific number of sensory inputs. In this paper we extend the proposed method so that considered the direction of correlation between the force and the velocity by using canonical correlations and it can be applied to arbitrary DOF systems with arbitrary number of sensory inputs.