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The purpose of this paper is to solve the ground verification and test method for space robot system capturing the target satellite based on visual servoing with time-delay in 3-dimensional space prior to space robot being launched.

To implement the approaching and capturing task, a motion planning method for visual servoing the space manipulator to capture a moving target is presented. This is mainly used to solve the time-delay problem of the visual servoing control system and the motion uncertainty of the target satellite. To verify and test the feasibility and reliability of the method in three-dimensional (3D) operating space, a set of ground hardware-in-the-loop simulation verification systems is developed, which adopts the end-tip kinematics equivalence and dynamics simulation method.

The results of the ground hardware-in-the-loop simulation experiment validate the reliability of the eye-in-hand visual system in the 3D operating space and prove the validity of the visual servoing motion planning method with time-delay compensation. At the same time, owing to the dynamics simulator of the space robot added in the ground hardware-in-the-loop verification system, the base disturbance can be considered during the approaching and capturing procedure, which makes the ground verification system realistic and credible.

The ground verification experiment system includes the real controller of space manipulator, the eye-in-hand camera and the dynamics simulator, which can veritably simulate the capturing process based on the visual servoing in space and consider the effect of time delay and the free-floating base disturbance.

In large-scale environments and unstructured scenarios, the accuracy and robustness of traditional light detection and ranging (LiDAR) simultaneous localization and mapping (SLAM) algorithms are reduced, and the algorithms might even be completely ineffective. To overcome these problems, this study aims to propose a 3D LiDAR SLAM method for ground-based mobile robots, which uses a 3D LiDAR fusion inertial measurement unit (IMU) to establish an environment map and realize real-time localization.

First, we use a normal distributions transform (NDT) algorithm based on a local map with a corresponding motion prediction model for point cloud registration in the front-end. Next, point cloud features are tightly coupled with IMU angle constraints, ground constraints and gravity constraints for graph-based optimization in the back-end. Subsequently, the cumulative error is reduced by adding loop closure detection.

The algorithm is tested using a public data set containing indoor and outdoor scenarios. The results confirm that the proposed algorithm has high accuracy and robustness.

To improve the accuracy and robustness of SLAM, this method proposed in the paper introduced the NDT algorithm in the front-end and designed ground constraints and gravity constraints in the back-end. The proposed method has a satisfactory performance when applied to ground-based mobile robots in complex environments experiments.

Jumping robots with coordinated multiple legs have been a hot research subject during the past years because of their excellent abilities in fast moving and obstacle-climbing. However, dynamics of jumping process of these coordinated legged robots are complex because of collisions between coordinated legs and the ground. This paper aims to analyze features of jumping process and to present the kinematic and dynamic models of a novel sole-type quadruped jumping robot with variable coordinated joints.

A complete jumping period of is divided into several subphases according to contact status of different coordinated legs to the ground. Continuous dynamics and discrete dynamics are established in different subphases. Simulations are performed in MATLAB software and ADAMS environment.

Comparison between two-set simulated results acquired from ADAMS and MATLAB demonstrates the validity of kinematic and dynamic equations.

The established dynamics establish the foundation of further research in motion planning and controller design of coordinated multiple legs.

This paper aims to develop a wave-transmitting mechanism for a travelling-wave-type omnidirectional mobile robot. Existing omnidirectional mechanisms are prone to movement instability because they establish a small contact area with the ground. The authors have developed a novel omnidirectional mobile robot that achieves stable movement by a large ground-contact area. The proposed robot moves by a wave-transmitting mechanism designed for this purpose.

To achieve stable movement, a spiral-type travelling-wave-propagation mechanism that mimics the locomotion mechanism of a snail was developed. The mechanism was applied to an omnidirectional mobile robot.

The practicality of magnetic attraction was verified in experiments of the wave-transmitting mechanism. Moreover, omnidirectional movement was confirmed in a robot prototype adopting this mechanism.

The proposed robot will eventually be deployed in human spaces such as factories and hospitals. A mechanically improved version of the robot will be evaluated in load-driving experiments and equipped with control systems.

This paper proposes an omnidirectional mobile robot with a large ground contact area that moves by continuous travelling waves. The practicability of this mechanism was experimentally confirmed, and a prototype robot achieved omnidirectional movement.

This paper aims to propose a method to solve the problem of localization and mapping of a two-wheeled inverted pendulum (TWIP) robot on the ground using the Stereo–inertial measurement unit (IMU) system. This method reparametrizes the pose according to the motion characteristics of TWIP and considers the impact of uneven ground on vision and IMU, which is more adaptable to the real environment.

When TWIP moves, it is constrained by the ground and swings back and forth to maintain balance. Therefore, the authors parameterize the robot pose as SE(2) pose plus pitch according to the motion characteristics of TWIP. However, the authors do not omit disturbances in other directions but perform error modeling, which is integrated into the visual constraints and IMU pre-integration constraints as an error term. Finally, the authors analyze the influence of the error term on the vision and IMU constraints during the optimization process. Compared to traditional algorithms, the algorithm is simpler and better adapt to the real environment.

The results of indoor and outdoor experiments show that, for the TWIP robot, the method has better positioning accuracy and robustness compared with the state-of-the-art.

The algorithm in this paper is proposed for the localization and mapping of a TWIP robot. Different from the traditional positioning method on SE(3), this paper parameterizes the robot pose as SE(2) pose plus pitch according to the motion of TWIP and the motion disturbances in other directions are integrated into visual constraints and IMU pre-integration constraints as error terms, which simplifies the optimization parameters, better adapts to the real environment and improves the accuracy of positioning.

Rapid satellite capture by a free-floating space robot is a challenge problem because of no-fixed base and time-delay issues. This paper aims to present a modified target capturing control scheme for improving the control performance.

For handling such control problem including time delay, the modified scheme is achieved by adding a delay calibration algorithm into the visual servoing loop. To identify end-effector motions in real time, a motion predictor is developed by partly linearizing the space robot kinematics equation. By this approach, only ground-fixed robot kinematics are involved in the predicting computation excluding the complex space robot kinematics calculations. With the newly developed predictor, a delay compensator is designed to take error control into account. For determining the compensation parameters, the asymptotic stability condition of the proposed compensation algorithm is also presented.

The proposed method is conducted by a credible three-dimensional ground experimental system, and the experimental results illustrate the effectiveness of the proposed method.

Because the delayed camera signals are compensated with only ground-fixed robot kinematics, this proposed satellite capturing scheme is particularly suitable for commercial on-orbit services with cheaper on-board computers.

This paper is original as an attempt trying to compensate the time delay by taking both space robot motion predictions and compensation error control into consideration and is valuable for rapid and accurate satellite capture tasks.

Heterogeneous teams consisting of unmanned ground vehicles and unmanned aerial vehicles are being used for different types of missions such as surveillance, tracking and exploration. Exploration missions with heterogeneous robot teams (HeRTs) should acquire a common map for understanding the surroundings better. The purpose of this paper is to provide a unique approach with cooperative use of agents that provides a well-detailed observation over the environment where challenging details and complex structures are involved. Also, this method is suitable for real-time applications and autonomous path planning for exploration.

Lidar odometry and mapping and various similarity metrics such as Shannon entropy, Kullback–Leibler divergence, Jeffrey divergence, K divergence, Topsoe divergence, Jensen–Shannon divergence and Jensen divergence are used to construct a common height map of the environment. Furthermore, the authors presented the layering method that provides more accuracy and a better understanding of the common map.

In summary, with the experiments, the authors observed features located beneath the trees or the roofed top areas and above them without any need for global positioning system signal. Additionally, a more effective common map that enables planning trajectories for both vehicles is obtained with the determined similarity metric and the layering method.

In this study, the authors present a unique solution that implements various entropy-based similarity metrics with the aim of constructing common maps of the environment with HeRTs. To create common maps, Shannon entropy–based similarity metrics can be used, as it is the only one that holds the chain rule of conditional probability precisely. Seven distinct similarity metrics are compared, and the most effective one is chosen for getting a more comprehensive and valid common map. Moreover, different from all the studies in literature, the layering method is used to compute the similarities of each local map obtained by a HeRT. This method also provides the accuracy of the merged common map, as robots’ sight of view prevents the same observations of the environment in features such as a roofed area or trees. This novel approach can also be used in global positioning system-denied and closed environments. The results are verified with experiments.

The collective intelligence emerging from behaviors of social insects has become an inspiration source that is impossible to avoid; guiding researchers in various domains to solutions of insolvent problems by traditional approaches. These behaviors are made possible because of the interactions individual‐individual and individual‐environment, representing support on which cooperative work within the same group is based and allowing emergence at macroscopic level of sophisticated achievements. Many models were inspired by this new and very promising vision, to find simple rules, leading mobile, autonomous robots with limited capacities in their environment to realize tasks, like those of: browsing, collecting or self‐assembly. In this context, the purpose of this paper is to suggest a method, making global behavior evolve within an homogeneous agent‐robots community to accomplish heap‐formation task based on appointment principle in changing environment which can be very difficult. Control device, comparable to the functioning of cellular automaton containing sensory‐motor rules, is then used to arbitrate between some given elementary attitudes with which each agent‐robot initially is equipped.

Evolutionary approach using genetic algorithm based on reverse emergence principle seeks, then, for cellular automaton whose arbitration succeeds to realize this adaptive oriented grouping task.

Rules as simulation results obtained according to reactive model of multi‐agent systems are provided, compared with those found at the ants and commented.

Discovered rules are adaptive; it means when training ground becomes more difficult, agent‐robots become more flexible by decreasing thresholds conditioning rules application. If environment state continues to turn into harsh, robots are able to seek for another direction to start new heap formation somewhere else. Such zones are like Saharan region, airports or supermarkets.

The computing power of the legged robot is not enough to perform high-frequency updates for the full-body model predictive control (MPC) of the robot, which is a common problem encountered in the gait research of the legged robot. The purpose of this paper is to propose a high-frequency MPC control method for the bounding gait of a parallel quadruped robot.

According to the bounding gait characteristics of the robot, the quadruped robot model is simplified to an equivalent plane bipedal model. Under the biped robot model, the forces between the robot’s feet and the ground are calculated by MPC. Then, the authors apply a proportional differential controller to distribute these forces to the four feet of the quadruped robot. The robot video can be seen at www.bilibili.com/video/BV1je4y1S7Rn.

To verify the feasibility of the controller, a prototype was made, and the controller was deployed on the actual prototype and then fully analyzed through experiments. Experiments show that the update frequency of MPC could be stabilized at 500 Hz while the robot was running in the bounding gait stably and efficiently.

This paper proposes a high-frequency MPC controller under the simplified model, which has a higher working efficiency and more stable control performance.

The aim of the research is the development of a small-scale ground mobile robot for surveillance and inspection; the main design goals are mobility in indoor environments with step climbing ability, pivoting around a vertical axis and without oscillations for stable vision, mobility in unstructured environments, low mechanical and control complexity.

The proposed hybrid leg-wheel robot is characterized by a main body equipped with two actuated wheels and two praying Mantis rotating legs; a rear frame with two idle wheels is connected to the main body by a vertical revolute joint for steering; a second revolute joint allows the rear axle to roll. The geometrical synthesis of the robot has been performed using a nondimensional approach for generality's sake.

The experimental campaign on the first prototype confirms the fulfilment of the design objectives; the robot can efficiently walk in unstructured environments realizing a mixed wheeled-legged locomotion.

Thanks to the operative flexibility of Mantis in indoor and outdoor environments, the range of potential applications is wide: surveillance, inspection, monitoring of dangerous locations, intervention in case of terroristic attacks, military tasks.

Different from other robots of similar size, Mantis combines high speed and energetic efficiency, stable vision, capability of climbing over high steps, obstacles and unevenness.