Continuum robots with structural compliance have promising potential to operate in unstructured environments. However, this structural compliance brings challenges to the controller design due to the existence of considerable uncertainties in the robot and its kinematic model. Typically, a large number of sensors are required to provide the controller the state variables of the robot, including the length of each actuator and position of the robot tip. In this paper, a model-free method based on an adaptive Kalman filter is developed to accomplish path tracking for a continuum robot using only pressures and tip position. As the Kalman filter operates only with a two-step algebraic calculation in every control interval, the low computational load and real-time control capability are guaranteed. By adding an optimal vector to the control law, buckling of the robot can also be avoided. Through simulation analysis and experimental validation, this control method shows good robustness against the system uncertainty and external disturbance, and lowers the number of sensors.

To date, most quadruped robots are either equipped with trunks that are rigid bodies or consist of blocks connected by passive joints. The kinematic performance of these quadruped robots is only determined by their legs. To release the mobility of trunks and enhance the performance of quadruped robots, this paper proposes a metamorphic quadruped robot with a moveable trunk (a planar six-bar closed-loop linkage), called MetaRobot I, which can implement active trunk motions. The robot can twist its trunk like natural quadrupeds. Through trunk twisting, the stability margin of the quadruped robot can be increased compared with that of a quadruped robot with a rigid trunk. The inner relationship between the stability margin and the twisting angle is analyzed in this paper. Finally, simulations are carried out to show the benefits facilitated by the twisting trunk to the quadruped robot.

The natural quadrupeds, such as geckos and lizards, often twist their trunks when moving. Conventional quadruped robots cannot perform the same motion due to equipping with a trunk which is a rigid body or at most consists of two blocks connected by passive joints. This paper proposes a metamorphic quadruped robot with a reconfigurable trunk which can implement active trunk motions, called MetaRobot I. The robot can imitate the natural quadrupeds to execute motion of trunk twisting. Benefiting from the twisting trunk, the stride length of this quadruped is increased comparing to that of conventional quadruped robots. In this paper a continuous static gait benefited from the twisting trunk performing the increased stride length is introduced. After that, the increased stride length relative to the trunk twisting will be analysed mathematically. Other points impacting the implementation of the increased stride length in the gait are investigated such as the upper limit of the stride length and the kinematic margin. The increased stride length in the gait will lead the increase of locomotion speed comparing with conventional quadruped robots, giving the extent that natural quadrupeds twisting their trunks when moving. The simulation and an experiment on the prototype are then carried out to illustrate the benefits on the stride length and locomotion speed brought by the twisting trunk to the quadruped robot.

A kinetostatic approach applied to the design of a backflip strategy for quadruped robots is proposed in this paper. Inspired by legged animals and taking the advantage of the leg workspace, this strategy provides an optimal design idea for the low-cost quadruped robots to achieve self-recovery after overturning. Through kinetostatic and energy analysis, a four-stepped backflip strategy based on the selected rotation axis with minimum energy is proposed, with a process of selection, lifting, rotating, and protection. The kinematic factors that affect the backflip are investigated, along with the relationship between the design parameters of the leg and trunk being analyzed. At the end of this paper, the strategy is validated by a simulation and experiments with a prototype called DRbot, demonstrating that the strategy endows the robot a strong self-recovery ability in various terrains.