For a small-sized biomimetic robot, it is challenging to mimic animal-like motion with high speed and high flexibility. To enable high flexibility, high stability, and high biomimicry degree for the robotic rat, we drew inspirations from three agile rat movements, namely, the pitch, yaw, and U-turn movements. First, we proposed key movement joints (KMJs) to capture a decent representation of the rat with a reduced-order model. By extracting the primary KMJs, we determined the number and distribution of robotic joints for the design of a bioinspired spine mechanism. Second, to meet the demand of high biomimicry degree, we generated an optimal compensation term to minimize the trajectory error introduced by simplifying the model. Moreover, we calculated the optimal minimum motion cycle based on the constraints of equilibrium under extreme conditions to ensure high flexibility without compromising the stability. Finally, the proposed method was successfully verified through simulation and experimental tests with a robotic rat endowed with the bioinspired spine mechanism.

Soft robotics has recently become a popular topic owing to its advantages over conventional rigid robotics. We introduce a soft robot that can grow with its own structure; its main components include an inflatable tube for its body and a tip with an expansion mechanism. The tube is made of conventional laminated film. It leads the robot to improved applicability. The robot can grow along the horizontal and vertical directions, and it can bend around yaw and pitch axis. To achieve this, a mechanism feeds air into the inflatable tube for growing the structure, and another heat welding mechanism allows producing bending points where necessary. The experimental results confirm that the proposed robot can grow in mid-air and bend around the yaw axis with varying bending radii. Further, the robot can climb a wall and displace an upper surface by pitch-axis bending. The designed bending structures are very stable because of heat welding; the growing and climbing capabilities depend on the inner pressure of the tube, and these capabilities allow the robot to select various shapes and move seamlessly in various environments.

Recently, flexible robots are growing in importance owing to their merits over rigid robots in maneuverability and safety, which equips them to work in unstructured environments, such as occur in medical applications. However, motion planning and control of flexible manipulators is challenging due to their compliance behavior and system uncertainties. Thus, this letter presents an Imitation-based Motion Planning (IbMP) approach, along with dynamic impedance control for learning, planning, and trajectory tracking of a two-section soft continuum robot in a dynamic environment. Point-to-point motion demonstrations, including the robot's tip position and orientation are intuitively provided by a motion capture system (OptiTrack V120-trio) and a similar kinematic flexible interface. Additionally, a singularity-free dynamic model based on Lagrangian formulation and Taylor expansion series of a two-section continuum robot is derived while planning for robot motions. The simulation results show that the IbMP approach, along with the dynamic impedance control, generalizes the robot's motion by varying the initial and goal of the robot's tip pose while avoiding static and dynamic obstacles, and moving back to the desired track after disturbances. Finally, the stability and performance of the IbMP algorithm against input disturbances are assessed using a Monte Carlo approach that can guide the selection of gain values.

EMG sensors for biomechanics research and portable applications need to be small, wireless and power efficient. This imposes several constraints on the design methodology of such sensors. There are many commercially available devices which are expensive and have proprietary communication protocols. It is difficult to synchronize them with other devices. Furthermore, using gel-based electrodes for signal acquisition increases setup time and running costs. Hence we present the design of a miniaturized, wireless, low-cost and non-invasive dry-electrode EMG sensor that was prototyped in our lab and dubbed the `WB-EMG' Sensor. We demonstrate its working being fitted with a gold plated copper core electrode. By mounting the sensor on the extensor carpiulnaris and recording data during some simple exercises, we were able to show that its envelope in the frequency domain was similar to the expected EMG Pattern.

Soft growing robots, a new soft mobile robot, have recently attracted considerable interest. There are many soft growing robots, some of which have irreversible growing and bending motion mechanisms. For such robots, path planning methods that provide information on bending timing improve operation efficiency. Although various path planning methods have already been developed, they cannot be applied to our growing robot that uses a heat welding mechanism because it has a constraint that all bending angles are the constant value. This letter proposes a novel path planning method with constant bending angle constraint. The proposed algorithm was developed based on the rapidly-exploring random tree star (RRT ^* ) algorithm. The method incorporates an algorithm for reducing unnecessary nodes from obtained paths keeping bending angles constant and improving path optimality. We confirmed that the proposed method generates paths whose bending angles are constant. In addition, we experimented with moving our robot along the path in the field with some obstacles. The result showed that the proposed method enabled the robot to reach to target place, avoiding obstacles. The proposed method improves the operating efficiency of our soft growing robot.