Cellular Robot Research Articles

Three-dimensional truss path planning of cellular robots based on improved sparrow algorithm

AbstractAs space missions are needed in the future, the assembly volume of the space truss will become larger and larger, and the advancing path of the on-orbit cellular robot to the mission target will become more and more complicated. If the shortest moving path cannot be found in the truss environment, the climbing time of the robot on the truss will be greatly increased. To improve the speed of the cellular robot moving to the target point on the large space truss, this paper designs a cellular robot structure and configuration suitable for climbing on the truss and uses the improved sparrow algorithm to solve the problem of robot motion path planning. By establishing a mathematical model of the space truss, the improved sparrow algorithm is used to find the shortest path between the starting point and the end point in the truss environment. Finally, the data of this algorithm are compared with the data of other algorithms. The data results show that the improved sparrow algorithm is very effective in solving the optimal path of the space truss. The improved sparrow algorithm keeps the same optimal path compared with the standard sparrow algorithm, and the overall reaction time is increased by 51.60%, and the number of effective iterations is increased by about 13.87%.

Milli-scale cellular robots that can reconfigure morphologies and behaviors simultaneously

Modular robot that can reconfigure architectures and functions has advantages in unpredicted environment and task. However, the construction of modular robot at small-scale remains a challenge since the lack of reliable docking and detaching strategies. Here we report the concept of milli-scale cellular robot (mCEBOT) achieved by the heterogeneous assembly of two types of units (short and long units). Under the magnetic field, the proposed mCEBOT units can not only selectively assemble (e.g., end-by-end and side-by-side) into diverse morphologies corresponding to the unstructured environments, but also configure multi-modes motion behaviors (e.g., slipping, rolling, walking and climbing) based on the on-site task requirements. We demonstrate its adaptive mobility from narrow space to high barrier to wetting surface, and its potential applications in hanging target taking and environment exploration. The concept of mCEBOT offers new opportunities for robot design, and will broaden the field of modular robot in both miniaturization and functionalization.

Research on Orbit Assembly Strategy of Large-scale Space Truss Structure

Background: With the rapid development of spatial technology and mankind's continuous exploration of the space domain, expandable space trusses play an important role in the construction of space station piggyback platforms. Therefore, the study of the in-orbit assembly strategy for space trusses has become increasingly important in recent years. The spatial truss assembly strategy proposed in this paper is fast and effective, and it is applied for the construction of future large-scale space facilities effectively. Objective: The four-prismatic truss periodic module is taken as the research object, and the assembly process of the truss and the assembly behaviors of the spatial cellular robot serving for on-orbit assembly are expressed. Methods: The article uses a reinforcement learning algorithm to study the coupling of truss assembly sequence and robot action sequence, then uses a q-learning algorithm to plan the strategy of the truss cycle module. Results: The robot is trained through the greedy strategy and avoids the failure problem caused by assembly uncertainty. The simulation experiment proves that the Q-learning algorithm of reinforcement learning used for planning the on-orbit assembly sequence of the truss periodic module structures is feasible, and the optimal assembly sequence with the least number of assembly steps obtained by this strategy. Conclusion: In order to address the on-orbit assembly issues of large spatial truss structures in the space environment, we trained the robots through greedy strategy to prevent failure due to the uncertainty conditions both in the strategy analysis and in the simulation study. Finally, the Q-learning algorithm in reinforcement learning is used to plan the on-orbit assembly sequence in the truss cycle module, which can obtain the optimal assembly sequence in the minimum number of assembly steps.

Spatial cellular robot in orbital truss collision-free path planning

Abstract. Aiming at the problem of moving path planning of a cellular robot on trusses in space station, a triangular prism truss is taken as the research object, and an optimized ant colony algorithm incorporating a gravitational search algorithm is proposed. The innovative use of the hierarchical search strategy which limits the exploration area, the use of gravity search algorithm to get the optimal solution of truss nodes, and further transform it into the initial value of pheromone in ant colony algorithm, can effectively prevent the algorithm from falling into the local optimal solution in the early stage, and make the optimization algorithm have a faster convergence speed. This paper proposes a heuristic function including the angle between the targets, which can effectively avoid blind search in the early stage and improve the ability of path search. The simulation results show that the path and planning time of the cellular robot can be effectively reduced when choosing truss path.

C-Balls: A Modular Soft Robot Connected and Driven via Magnet Forced

This paper describes a cellular robot(C-Balls) consisting of soft spherical modules with on-board actuation, power, computation and wireless control system. The robot modules maintain connection and realize relative movement by utilizing magnetic force and friction force between driving units inside the soft modules. Preliminary tests of locomotion and deformation of the robot are proposed. The rolling experiment displays the mobility of the robot of two spherical modules. The deforming experiments indicate that the robot with five spherical modules deforms from linear to circular configuration successfully. Further more, a climbing experiment is conducted, which shows the robot can climb on various surfaces including soft materials.

Three-dimensional control of Tetrahymena pyriformis using artificial magnetotaxis

We demonstrate three-dimensional control with the eukaryotic cell Tetrahymena pyriformis (T. pyriformis) using two sets of Helmholtz coils for xy-plane motion and a single electromagnet for z-direction motion. T. pyriformis is modified to have artificial magnetotaxis with internalized magnetite. To track the cell’s z-axis position, intensity profiles of non-motile cells at varying distances from the focal plane are used. During vertical motion along the z-axis, the intensity difference is used to determine the position of the cell. The three-dimensional control of the live microorganism T. pyriformis as a cellular robot shows great potential for practical applications in microscale tasks, such as target transport and cell therapy.

Characterization of Deciliation-Regeneration Process of Tetrahymena Pyriformis for Cellular Robot Fabrication

Artificial magnetotactic Tetrahymena pyriformis GL ( T. pyriformis) cells were created by the internalization of iron oxide nano particles and became controllable with a time-varying external magnetic field. Thus, T. pyriformis can be utilized as a cellular robot to conduct micro-scale tasks such as transportation and manipulation. To complete these tasks, loading inorganic or organic materials onto the cell body is essential, but functionalization of the cell membrane is obstructed by their motile organelles, cilia. Dibucaine HCl, a local anesthetic, removes the cilia from the cell body, and the functional group would be absorbed more efficiently during cilia regeneration. In this paper, we characterize the recovery of artificial magnetotactic T. pyriformis after the deciliation process to optimize a cellular robot fabrication process. After sufficient time to recover, the motility rate and the average velocity of the deciliated cells were six and ten percent lower than that of non-deciliated cells, respectively. We showed that the motile cells after recovery can still be controlled using magnetotaxis, making T. pyriformis a good candidate to be used as a cellular robot.

Study of Group Robots Adaptively Forming a Mechanical Structure. Effect of Mechanical Properties of Cellular Robots on Structure Formation.

In this paper, group robots which can adaptively form a mechanical structure are described. The group robots consist of identical cellular robots. Each cellular robot has the identical mechanical structure and autonomous behavior. In the situation considered in this study, a mobile object must cross over from one cliff to another in the absence of a bridge. The mission of the group robots is to form a mechanical bridge-like structure which is governed by the movement of the object. This paper focuses on the mechanical specifications required for the cellular robots for execution of the mission. We pointed out that three mechanical parameters for the sensing stress of the cellular robot are essential for formation of the structure. The structure formation process was examined by computer simulations for discussing the effects of the mechanical parameters.

Study of Group Robots Adaptively Forming a Mechanical Structure. Information-Processing Functions of the Cellular Robot Required for Transporting a Load to an Opposite Side.

This study deals with autonomous distributed robots that are able to adaptively construct a structure in response to a loading condition. The simulation consists of identical components (cellular robots). Each cellular robot has functions for sensing, communication and motion. In this paper, we discuss the following situation. There is a gap on the ground. A moving load lies at one side but cannot reach the opposite side. The mission of the cellular robots is to help the moving load pass over the gap by forming a bridge-like mechanical structure. After finishing the mission, they must return to their original place. We examined the information processing required of the cellular robots to execute the mission and proposed algorithms based on local rules. Using these algorithms, we simulated the group behavior of the cellular robots on a computer and demonstrated validity.

Vision-based remote control of cellular robots

This paper describes the development and design of a vision-based remote controlled cellular robot. Cellular robots have numerous applications in industrial problems where simple inexpensive robots can be used to perform different tasks that involve covering a large working space. As a methodology, the robots are controlled based on the visual input from one or more cameras that monitor the working area. As a result, a robust control of the robot trajectory is achieved without depending on the camera calibration. The remote user simply specifies a target point in the image to indicate the robot final position. We describe the complete system at various levels: the visual information processing, the robot characteristics and the closed loop control system design, including the stability analysis when the camera location is unknown. Results are presented and discussed. In our opinion, such a system may have a wide spectrum of applications in industrial robotics and may also serve as an educational testbed for advanced students in the fields of vision, robotics and control.

Study of Group Robots Adaptively Forming a Mechanical Structure. Information Processing Functions of the Cellular Robot Required for Transporting a Load to an Opposite Side.

This study deals with autonomous distributed robots adaptively forming a structure for a loading condition. The simulation model consists of identical components (cellular robots). Each cellular robot has some functions about sensing, communication and mobility. In this paper, we discuss the following subject. There is a gap on the ground. A moving load lies at one side, but can not reach the opposite side. Mission of the cellular robots is to help the moving load to pass over the gap forming a structure like a bridge by themselves. After finishing the mission, they must return to the original place. We examined the required information processing of the cellular robots for execution of the mission and proposed the algorithms based on local rules. Using the algorithms, we simulated group behavior of the cellular robots on a computer and showed the validity.

Study of Group Robots Adaptively Forming A Mechanical Structure. Effect of Mechanical Properties of Cellular Robots on Forming the Structure.

This paper describes group robots which adaptively forms a mechanical structure. The group robots consist of identical cellular robots. Each cellular robot has same mechanical structure and control functions. We examined the specs of the cellular robots to generate harmonized grouping behavior by themselves under the following condition. There is a cliff on the ground, where a substance is going to move forward. The mission of the group robots is to support the substance by forming a mechanical structure like a bridge according to the movement. This paper mainly discussed the mechanical specs of the cellular robot required for execution of the mission. We pointed out that three mechanical parameters on sensing stress of the cellular robot are essential for formation of the structure. The formation of the structure was examined by computer simulations discussing the effect of the mechanical parameters.