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This paper presents a problem of odor source localization in a dynamic environment, which means the odor distribution is changing over time. Most work on chemical sensing with mobile robots assume an experimental setup that minimizes the influence of turbulent transport by either minimizing the source-to-sensor distance in trail following or by assuming a strong unidirectional air stream in the environment, including our previous work. However, not much attention has been paid to the natural environment problem. Modification Particle Swarm Optimization is a well-known algorithm, which can continuously track a changing optimum over time. PSO can be improved or adapted by incorporating the change detection and responding mechanisms for solving dynamic problems. Charged PSO, which is another extension of the PSO, has also been applied to solve dynamic problems. Odor source localization is an interesting application in dynamic problems. We will adopt two types of PSO modification concepts to develop a new algorithm in order to control autonomous vehicles. Before applying the algorithm for real implementation, some important hardware conditions must be considered. Firstly, to reduce the possibility of robots leaving the search space, a limit to the value of velocity vector is needed. The value of vector velocity can be clamped to the range [-Vmax, Vmax]; in our case for the MK-01 Robot, the maximum velocity is 0.05 m/s. Secondly, in the standard PSO algorithm there is no collision avoidance mechanism. To avoid the collision among robot we add some collision avoidance functions. Finally, we also add some sensor noise, delay and threshold value to model the sensor response. Then we develop odor localization algorithm, and simulations to show that the new approach can solve such dynamic environment problems.

In electronic manufacturing systems, the design of the robotic hand is important for successful accomplishment of the assembly task, and also for human and robot coworker coordinated assembly. Due to the restrictions on the architecture of traditional robotic hands, the status of assembly parts, such as position and rotation during the assembly process cannot be detected effectively. In this research, an intelligent robotic hand – i-Hand, equipped with multiple small sensors – is designed and built for this purpose. Mating connectors by robot, as an experimental case in this paper, is studied to evaluate i-Hand performance. A new model that converts the traditional time-zone-driven model to an event-driven model is proposed to describe the process ofmating connectors, within which, most importantly, the distance between the connector and deformable Printed Circuit Board (PCB) is detected by i-Hand. The generated curve has provided more robust parameters than our previously studied Fault Detection and Diagnosis (FDD) classifier. Various possible situations during assembly are considered and handled based on this event-driven work flow. The effectiveness of our proposed model and algorithm is proven in experiments.

In previous works, an intelligent cane robot was proposed to assist the elderly or persons with conditions that slightly restrict their motion ability. The cane robot can help the elderly walk in both indoor and outdoor environments because of its miniaturized design and mobility. In the intentional direction (ITD) concept the user’s walking intention is estimated by analyzing signals from a six-axis force/torque sensor. An admittance control method controls the motion of the cane robot. In some cases, however the elderly can not walk uniformly because one leg suffers from muscular weakness. When the affected leg is in the support phase, the cane robot should stop to absorb more strain than the affected leg. When the healthy leg is in the support phase, the cane robot should move forward according to ITD. In contrast to ITD, the motion of the cane robot should be controlled considering the walking pattern characteristics of the elderly to ensure safety and effectiveness. In this paper, an optimizedmotion control of the cane robot is proposed that is based on the characteristics gait pattern (CGP). An on-shoe load sensor was used to evaluate the reduction in muscular fatigue for the user’s affected leg. The effectiveness of the proposed method was verified through experiments.