This paper studies a novel fluid actuated system for a spherical mobile robot. The robot’s mechanism consists of two essential parts: circular pipes to lead spherical moving masses (cores) and an internal driving unit to propel the cores. The spherical shell of the robot is rolled by displacing the cores in the pipes filled with fluid. First, we describe the structure of the robot and derive its nonlinear dynamics using the D’Alembert principle. Next, we model the internal driving unit that actuates the core inside the pipe. The simulated driving unit is studied with respect to three important parameters—the input motor torque, the actuator size, and the fluid properties. The overall model of the robot is then used for analyzing motion patterns in the forward direction. Analytical studies show that the modeled robot can be implemented under the given design specifications.

This paper presents a state-of-the-art approach in object detection for being applied in future SLAM problems. Although, many SLAM methods are proposed to create suitable autonomy for mobile robots namely ground vehicles, they still face overconfidence and large computations during entrance to immense spaces with many landmarks. In particular, they suffer from impractical applications via sole reliance on the limited sensors like camera. Proposed method claims that unmanned ground vehicles without having huge amount of database for object definition and highly advance prediction parameters can deal with incoming objects during straight motion of camera in real-time. Line-Circle (LC) filter tries to apply detection, tracking and learning to each defined experts to obtain more information for judging scene without over-calculation. In this filter, circle expert let us summarize edges in groups. The Interactive feedback learning between each expert creates minimal error that fights against overwhelming landmark signs in crowded scenes without mapping. Our experts basically are dependent on trust factors' covariance with geometric definitions to ignore, emerge and compare detected landmarks. The experiment for validating the model is taken place utilizing a camera beside an IMU sensor for location estimation.

In this paper, the rest-to-rest motion planning problem of a fluid-actuated spherical robot is studied. The robot is driven by moving a spherical mass within a circular fluid-filled pipe fixed internally to the spherical shell. A mathematical model of the robot is established and two inverse dynamics-based feed-forward control methods are proposed. They parameterize the motion of the outer shell or the internal moving mass as weighted Beta functions. The feasibility of the proposed feed-forward control schemes is verified under simulations.

There are important issues in the design of the driving mechanism for the rolling robots. The actuator is expected to operate without occupying the whole space of the carrier body. This property gets harder to achieve as the degree of freedom in driving mechanism increases. This paper proposes an alternative fluid actuator for rolling bodies e.g., sphere or disc. The designed mechanism has a circular pipe that is propelled by rotating spherical mass (core) inside a fluid medium. In this work, we first establish the dynamics of the rolling circular pipe. Then, the internal driving unit is modeled and combined with rotating mass dynamics. Finally, the model simulations are conducted for observing motion patterns of the carrier body and locomotion abilities of the rotating core. The results show the feasibility of the proposed actuator for future applications.

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