Continuum robots, known for their compliance in unstructured environments, face limitations due to the lack of rotational degrees of freedom (DOFs) about the backbone. This prevents them from compensating undesired torsional deformation and performing 6-DOF control of the end-effector, thereby restricting their mobility. This paper presents a continuum robot with integrated dual rotational DOFs. One is integrated at the arm base to compensate for torsional deformation caused by external loads, while the other one, located at the arm tip, enables full 6-DOF control of the end-effector. To control the robot, a screw-theory-based kinematic model and a kinematic control framework are proposed to enable real-time, simultaneous control of the end-effector’s position and orientation. Experimental results show that the arm base rotational joint can fully compensate for undesired torsional deformation caused by a 1000 g payload. Thanks to the arm tip’s DOF and the proposed kinematic control framework, the robot’s end-effector can maintain a constant orientation while achieving open-loop path-tracking errors of only 3.3% of the arm’s length (930 mm), and successfully executing valve-closing tasks with coordinated 6-DOF motion, demonstrating the robot’s potential for industrial maintenance, human-robot interaction, and confined-space manipulation.

Dynamic capture is one of the most challenging issues to be solved in the field of robotics. Although robotic hands/grippers have emerged for decades, there are still few of them that can dynamically capture moving targets because the process is strongly accompanied by impact force and uncertainties in relative gripper/target locations and velocities. In this article, we present the novel design of a multitentacle gripper inspired by the motions of sea anemones. It is found that each tentacle of the sea anemone is not individually able to capture a fish but the collaboration of a larger number of tentacles can greatly enhance the overall capture ability. Based on this concept, 12 continuum arms including active and passive types are proposed and evaluated for their deformation to external forces. In addition, a deployable base, inspired by origami and Sarrus mechanisms, is utilized to change the posture of the continuum arms and drive the active arms. An inertial measurement unit is equipped to sense the impact of the dynamic targets. Finally, a series of experiments proved that the proposed multitentacle gripper could capture dynamic targets with different shapes, velocities, and collision angles, showing satisfactory capture robustness.

As a traditional movement assist equipment for people with lower-limb dysfunction, the wheelchair can support and carry users to perform a long-distance movement indoor and outdoor, however, prolonged inactivity can lead to muscle atrophy and deteriorate motion functions. As a promising solution, the lower limb exoskeleton provides people the ability of standing and walking to avoid these problems. However, the exoskeleton has inevitable shortcomings in long-distance movement and balance, which do not exist in a wheelchair. To integrate the advantages of both devices, in this paper, we proposed a wheelchair-exoskeleton hybrid robot (WeHR) that can not only provide users long-time support and long-distance movement but also provide walking training and keep self-balance. Moreover, motion transitions such as sit-to-stand and stand-to-sit can also be implemented by the newly proposed device without help from caregivers. We have developed the prototype to implement the above functions. In this paper, we emphasize the strategy of motion transition including two trajectory planning methods for the Sit-To-Stand (STS) process as well as the mechanism design to implement it. Furthermore, the preliminary experiments of motion transition and walking test are also conducted and the results prove that our device can support users sitting, standing, and walking and the motion transition.

Precise actuation of continuum surfaces in combination with continuum robotic arms that undergo large deformation is of high interest in soft robotics but of limited model-based study to date. This work develops this area towards enabling the robust design and control of large deformation continuum surfaces (LDCS) across multiple industrial applications in the healthcare, aerospace, manufacturing, and automotive domains. It introduces an actuation based dynamic model of LDCSs to accurately determine their deflection due to application of concentrated external forces while maintaining many physical characteristics and constraints on actuation elements and surface structure such as gravity, inertia, damping, elasticity, and interactive forces between actuators and LDCS. Using the lumped-mass methodology, a 3D integrated surface-arm model is developed, simulated and then validated experimentally where a pair of parallel arms are attached to the surface to actuate and deform it. The surface is then simultaneously subjected to a concentrated constant external force at its top center between the two arms. Comparing measured displacements between the experimental and modelling results over actuation time yielded the maximum error is less than 1% of the length of the surface's side at its final deflected profile despite the limited number of nodes (masses) used in the LDCS model while it is exposed to a significant external force.

Octopus arms, as well as elephant trunks, squid tentacles, and vertebrate tongues are termed muscular-hydrostats. In such structures, the volume of the organ remains constant during their motions, enabling diverse, complex, and highly controlled movements without the support of a skeleton. Such flexible structures show major advantages over articulated arms that have a rigid skeleton and joints. These advantages have been attracting roboticists aiming to apply these material properties to soft robot controls. In this paper, we show that the muscular-hydrostat system itself has the computational capacity to achieve a complex nonlinear computation. By using a 3D dynamic simulator of the system inspired by the octopus, we actually demonstrate that the system is capable of emulating complex nonlinear dynamical systems by exploiting its elastic body dynamics as a computational resource. In addition, we systematically analyze its computational power in terms of memory capacity, and show that the system has an intrinsic and characteristic short term memory profile. Finally, the implications for soft robot control and future application scenarios are discussed.

This paper presents an Octopus inspired walking robot with pneumatic muscle actuator (PMA) driven continuum arms. Each arm is made up of 4 longitudinally arranged PMAs, consistent with octopus arm anatomy. We first present the design and construction of a single continuum arm followed by its modeling and experimental validation. The design of the walking robot is then presented followed by details of extended dynamic model describing the full walking robot with four arms. Basic control architecture is introduced for the robot to achieve walking motion and experimental results analyzed. Initial results show good agreement between the experimental results and simulation results.

Conventional rigid body robots typically use few degrees of freedom (DOF). This results in a manipulator that lacks flexibility and maneuverability when compared to continuum robots that utilize a much higher number of DOF. However, due to their continuous nature, the difficulty of measuring and controlling a large number of actuated DOF, and their high degree of nonlinearity, the development of control algorithms for continuum robot manipulators is an ongoing challenge. This paper presents an algorithm inspired by biological solutions from live octopus that utilizes division of functionality to achieve simple and robust control of continuum arm based systems. Simulated results for single and multiple dynamic continuum arms show the controller is capable of producing motions similar to that of octopus. The resulting controller is also computationally efficient enough for real-time implementation. In future this work will be implemented on a prototype robot with multiple continuum arms.

Continuum structures with a very high or infinite number of degrees of freedom (DOF) are very interesting structures in nature. Mimicking this kind of structures artificially is challenging due to the high number of required DOF. This paper presents a kinematic and dynamic model for an underwater robotic manipulator inspired by Octopus vulgaris. Then, a prototype arm inspired by live octopus is presented and the model validated experimentally. Initial comparisons of simulated and experimental results show good agreement.

Soft robots are difficult to control because of their compliant and elastic body dynamics compared with robots made of rigid bodies. In this paper, we present a control scheme inspired by the octopus called timing-based control for soft robotic arms. This control scheme is motivated to positively exploit the natural dynamics of the soft body. We demonstrate a scheme for controlling an object-reaching task by using an echo state network on a 3D physical soft robotic arm simulator and show that this network can successfully perform the task. Detailed analyses and evaluations of the generalization capacity of the network and the performances to the reaching task are presented.

This paper presents a control algorithm to achieve crawling locomotion for a multi-arm robotic system inspired by live octopuses. First the paper introduces a dynamic model of a continuum arm. The model accounts for the key features relevant to crawling locomotion, namely longitudinal muscles and suckers that provide force interaction with the surrounding environment. This single arm model is then validated against live octopus data and expanded to an 8-arm system. Appropriate coordination algorithms of the eight arms result in crawling locomotion. The results of this work can be used to study the motor control schemes for both multiple continuum arm robots and live octopuses.

The octopus arm is a unique tool that combines strength and flexibility. It can shorten, elongate and bend at any point along its length. To model this behavior, a hyper-redundant manipulator composed of multiple segments is proposed. Each segment is a parallel robotic mechanism with redundant actuation. The kinematics and dynamics of this manipulator are analyzed and simulated utilizing a modular computational modeling method. Simulation results for some primitive movements are presented, and the effect of hydrodynamic forces is included.