The underground building environment plays an increasingly important role in the construction of modern cities. To deal with possible fires, collapses, and so on, in underground building space, it is a general trend to use rescue robots to replace humans. This paper proposes a dual‐robot system solution for search and rescue in an underground building environment. To speed up rescue and search, the two robots focus on different tasks. However, the environmental perception information and location of them are shared. The primary robot is used to quickly explore the environment in a wide range, identify objects, cross difficult obstacles, and so on. The secondary robot is responsible for grabbing, carrying items, clearing obstacles, and so on. In response to the difficulty of rescue caused by unknown scenes, the Lidar, inertial measurement unit and multiview cameras are integrated for large‐scale 3D environment mapping. The depth camera detects the objects to be rescued and locate them on the map. A six‐degree‐of‐freedom manipulator with a two‐finger gripper is equipped to open doors and clear roadblocks during the rescue. To solve the problem of severe signal attenuation caused by reinforced concrete walls, corners and long‐distance transmission, a wireless multinode networking solution is adopted. In the case of a weak wireless signal, the primary robot uses autonomous exploration for environmental perception. Experimental results show the robots' system has high reliability in over‐the‐horizon maneuvering, teleoperation of the door opening and grasping, object searching, and environmental perception, and can be well applied to underground search and rescue.

For the Endoscope-assisted Surgical Robot system, the success of the surgery can be heavily determined by the accuracy of the unknown hand-eye matrix between the manipulator and the laparoscopic camera. Although many analytical solutions algorithms have been proposed, it is found that the hand-eye matrix estimated by some existing analytical solutions algorithms will deviate from its true value in some cases. Therefore, the singularity analysis for the solution of the hand-eye calibration based on orthogonal dual tensor is firstly pointed out in this paper. To avoid the above singular phenomenon, a novel singular-free solution based on Principle of Transfer theory is proposed in this paper, which can be verified by the corresponding simulation and experimental results.

Purpose This paper aims to present a new method to analyze the robot’s obstacle negotiation based on the terramechanics, where the terrain physical parameters, the sinkage and the slippage of the robot are taken into account, to enhance the robot’s trafficability. Design/methodology/approach In this paper, terramechanics is used in motion planning for all-terrain obstacle negotiation. First, wheel/track-terrain interaction models are established and used to analyze traction performances in different locomotion modes of the reconfigurable robot. Next, several key steps of obstacle-climbing are reanalyzed and the sinkage, the slippage and the drawbar pull are obtained by the models in these steps. In addition, an obstacle negotiation analysis method on loose soil is proposed. Finally, experiments in different locomotion modes are conducted and the results demonstrate that the model is more suitable for practical applications than the center of gravity (CoG) kinematic model. Findings Using the traction performance experimental platform, the relationships between the drawbar pull and the slippage in different locomotion modes are obtained, and then the traction performances are obtained. The experimental results show that the relationships obtained by the models are in good agreement with the measured. The obstacle-climbing experiments are carried out to confirm the availability of the method, and the experimental results demonstrate that the model is more suitable for practical applications than the CoG kinematic model. Originality/value Comparing with the results without considering Terramechanics, obstacle-negotiation analysis based on the proposed track-terrain interaction model considering Terramechanics is much more accurate than without considering Terramechanics.