It is empirically known that the stability of limit cycle gaits is dramatically improved by partly applying trajectory tracking control. This paper considers the model of an underactuated biped robot and investigates the stability of the gait strictly controlled to follow the desired-time trajectory of the hip angle using the linearized model. First, we derive the transition function for the state error of the stance phase, and analytically solve the stability condition and optimal solution. Second, we exactly show the stability of the collision phase and derive the sufficient condition for the limit cycle stability. Finally, the validity of the theoretical results is verified through numerical simulations.
In this paper, we propose a method for 3-D environment model construction based on structure from motion by using an omnidirectional camera. Map information is important for path planning and self-localization when mobile robots execute autonomous tasks. In an unknown environment, mobile robots should measure the environment and construct its map by themselves. Our proposed method uses point and line features to measure environments densely. Point and line feature-combined constraint condition make it possible to estimate camera movement precisely. Moreover, the proposed method optimizes baseline length for precision and robustness of camera movement estimation. The baseline optimization is invariant for environments, the number of features and camera movement. Experimental results show the effectiveness of our proposed method.
In dexterous micromanipulation, we need multi-beam optical tweezers which can manipulate multiple objects at once. Time-shared Scanning (TSS) and phase modulation of laser are typical multi-beam control methods. TSS can manipulate a few objects in high speed; on the other hand, the methods using phase modulation can manipulate a lot of objects in slow speed. In this research, we propose integration of these heterogeneous methods to improve manipulability of previous optical tweezers. We named this system Integrated Optical Tweezers. We designed and built the optical system and the control system totally. In the optical system, we used Generalized Phase Contrast (GPC) as phase modulation method and fabricated phase contrast filter with micro-fabrication technique. In the control system, we applied unilateral and bilateral teleoperation system. For the bilateral teleoperation, we propose force measurement method which has femto newton resolution. With the built system, we evaluated the performance and usefulness numerically or experimentally. We concluded this concept of integration system is helpful for practical situation.
This paper propose a novel stabilization method for power assist systems. It is important to stabilize power assist systems for safety, including a human operator and his motion. In this paper, a method for stabilizing the operational force into power assist systems is proposed, in terms of human visuospatial characteristics. It is known that the human motion affected by his vision. The proposed method is based on measurement and analysis of effects by user's line of sight on operational force to control power assist systems. The relationship between user's operational forces and the line of sight is considered designing the stabilization method using fuzzy regression analysis. Experiments and simulations to evaluate the proposed method are carried out, resulting the stabilization of operational force and motion of end-effecter of the system.
Nowadays, automation techniques for agriculture are being urgent tasks. In this paper, an Unmanned Ground Vehicle (UGV) in orchard is proposed as a base platform for monitoring trees, pesticide spraying, harvesting and so on. The control system is composed by a localization method in an orchard using 2D laser range finder and a map of trees, a robust control law based on nonlinear control theory, and a path regeneration algorithm to giude the vehicle smoothly to the target path. Experimental results in an orchard using a by-wire vehicle to which the control algorithm is applied are reported.
It is expected that robot technology is applied to some mission on rough terrain, for example,rescue activity and planetary explorer. Tracked vehicles are effective against such environment because contact pressure can be distributed wider. In order to get some progress of the tracked vehicle, we have proposed a mechanism, “Flexible Mono-tread mobile Track (FMT)”. FMT has only one track which wraps around the vehicle body, and the body flexes in shape flexibly in three dimensions when the vehicle turns, climbs up and down stairs, and so on. Pressure distribution in the contacting surface of FMT on the ground varies depending on its configuration, thereby a property of compounded centre of gravity movement varies. However, geometrical centre of its tread belt decides travel path. Hence, the property should be took in consideration for control and its autonomy. In the paper, a dynamic model for the FMT is derived in sagittal and lateral planes to treat the movements. Then, some simulation are shown to analyse the lateral movement with respect to various pressure distribution affected by the retro-flexion. Finally, the analysis is validated through some experiments.
This paper describes methods of environmental mapping and plane detection for daily assistive robots. Under the assumption that 3D information of around environment is constructed by collecting range data gradually measured, we propose an effective map representation named TCCM (Time-series Composite Cuboid Map). The method copes with temporal sequence explicitly, and map updating is efficiently performed. In addition, two plane estimation methods are proposed. Through experiments in daily environment, we ensured the effectiveness of our methods.