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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.

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.

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.

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.

The paper aims to improve the radiation-proof capability of the self-designed mobile robot with a 7-DOF manipulator, enabling the long-playing inspection and intervention under high-dose radiation environment. In this context, gamma-ray irradiation test for electronic components and specific hardness design have also been specifically presented and discussed.

The study’s hardness design mainly focuses on shielding protection, distance protection and time protection. Irradiation test is first carried out to investigate irradiation resistance of each electronic module. Then, modular deployment and shielding calculation are completed for the point-type nuclear accidents, respectively, to achieve a robust anti-radiation design scheme. Finally, the field experiment is conducted to validate system effectiveness and good mobility, and operational practices are acquired for the realization of time protection.

Coupled with modular redeployment and shielding design, irradiation results illustrate the effectiveness of robotic anti-radiation design. Meanwhile, experiences and reformed measures from the field exercise implement efficient operation and radiological time protection.

Considering the huge risks of high-dose source exposure, the radiation-resistance of the overall system cannot be verified in the field experiment. Fortunately, irradiation test and modular shielding calculation are conducted as a minimal validation.

The proposed anti-radiation design methods and the irradiated results can be applied to many other nuclear vehicles and manipulators for the feasible multi-layer protection and excellent mobility.

A nuclear intervention robot with specific hardness design is presented in detail in this paper. Enlightened by the idea of shielding and distance protection, a large number of electronic modules with multiple types and structures are treated and compared in irradiation experiments, while modular redeployment and retrofitting are completed to reduce irradiated damages. To achieve the effect of time protection, mobility performance and operational practices are discussed and validated in the field experiment based on the mobile system.

To solve the obstacle detection problem in robot autonomous obstacle negotiation, this paper aims to propose an obstacle detection system based on elevation maps for three types of obstacles: positive obstacles, negative obstacles and trench obstacles.

The system framework includes mapping, ground segmentation, obstacle clustering and obstacle recognition. The positive obstacle detection is realized by calculating its minimum rectangle bounding boxes, which includes convex hull calculation, minimum area rectangle calculation and bounding box generation. The detection of negative obstacles and trench obstacles is implemented on the basis of information absence in the map, including obstacles discovery method and type confirmation method.

The obstacle detection system has been thoroughly tested in various environments. In the outdoor experiment, with an average speed of 22.2 ms, the system successfully detected obstacles with a 95% success rate, indicating the effectiveness of the detection algorithm. Moreover, the system’s error range for obstacle detection falls between 4% and 6.6%, meeting the necessary requirements for obstacle negotiation in the next stage.

This paper studies how to solve the obstacle detection problem when the robot obstacle negotiation.