Compared with rigid grippers, soft grippers show fantastic adaptability and flexibility in grasping irregularly shaped and fragile objects. However, the low stiffness of the soft actuator limits the scope of applications. Particle jamming has emerged as an important method to adjust the stiffness of soft grippers. This paper proposes a novel particle jamming mechanism based on the differential pressure drive. With the differential drive particle jamming mechanism, a soft actuator is designed, which is characterized by a dual-deformable chamber structure in which one chamber is filled with particles. The simultaneous inflation of the two chambers will result in the bending behavior without significant stiffening. However, if the air chamber is pressurized with a larger pressure, the differential pressure will cause the particles inside the particle chamber to jam each other, which increases the stiffness of the actuator significantly. Thus, the differential drive particle jamming mechanism can achieve the independent control of the stiffness and the bending angle. Both theoretical and experimental studies in this area have shown that the gripper based on the differential drive particle jamming mechanism can stiffen itself effectively, and achieve the independent control of the stiffness and the bending angle, which can be adopted in applications where both high stiffness and dexterity are required.

Compared with traditional rigid robots, soft robots have high flexibility, low stiffness, and adaptability to unstructured environments, and as such have great application potential in scenarios such as fragile object grasping and human machine interaction. Similar to biological muscles, the soft actuator is one of the most important parts in soft robots, and can be activated by fluid, thermal, electricity, magnet, light, humidity, and chemical reaction. In this paper, existing principles and methods for actuation are reviewed. We summarize the preprogrammed and reprogrammed structures under different stimuli to achieve motions such as bending, linear, torsional, spiral. and composite motions, which could provide a guideline for new soft actuator designs. In addition, predominant manufacturing methods and application fields are introduced, and the challenges and future directions of soft actuators are discussed.

Due to the wide distribution and high energy-saving potential of industrial robots, energy optimization techniques of industrial robots attract increasing attention. Dynamic time-scaling methods can optimize the energy consumption of robots only by stretching or shrinking reference trajectories in the time dimension. Dynamic time-scaling methods show advantages over other energy-saving techniques because time-scaling methods can achieve energy savings without hardware investment. Traditional dynamic time-scaling methods need to search the possible state transitions from the initial configuration to the final configuration to obtain the optimal solution. The integration of robot transient power has to be carried out for each possible state transition, which directly leads to intensive computation. Therefore, in this article, an efficient computation method for robot trajectory optimization is proposed. Based on parameter separation, an energy characteristic parameter model based on the dynamic time-scaling is developed, which describes the energy consumption during the state transition as a function of the scaling parameters. Based on the energy characteristic parameter model, the dynamic programming algorithm can replace the integral operation of transient power with the substitution calculations, which avoids intensive computation. Experimental results show that the proposed method can achieve 33.7% less energy consumption, and the computation time can be reduced by nearly 99%.

Soft wall-climbing robots have been limited in their ability to perform complex locomotion in diverse environments due to their structure and weight. Thus far, soft wall-climbing robots with integrated functions that can locomote in complex 3-D environments are yet to be developed. This article addresses this challenge by presenting a lightweight (2.57 g) soft wall-climbing robot with integrated linear, turning, and transitioning motion capabilities. The soft robot employs three pneumatic bending actuators and two adaptive electroadhesion pads, which enable it to flip forward, transition between two walls, turn in two directions, and adhere to various surfaces. Different motion and control strategies are proposed based on a theoretical model. The experimental results demonstrate that the robot can move at an average speed of 3.85 mm/s (0.08 body length/s) on horizontal, vertical, and inverted walls and make transitions between walls with different pinch angles within 180°. Additionally, the soft robot can carry a miniature camera on vertical walls to perform detection and surveillance tasks. This article provides a reliable structure and control strategy to enhance the multifunctionality of soft wall-climbing robots and enable their applications in unstructured environments.