83 research outputs found
Variable stiffness actuator
No full textIt is provided a variable stiffness actuator (1) adapted to move a movable component (102) and comprising: two electric motors (4) of the rotary type, at least one output shaft (3) adapted to be set in rotation by said two electric motors (4) around a rotation axis (3a); an elastic transmission system adapted to enable motion transfer from said motors (4) to said output shaft (3) and to vary the stiffness of said output shaft (3); a control unit (9) adapted to adjust at least the stiffness of said output shaft (3) through said elastic transmission system; and a holding structure (2) defining an outer surface and an inner volume (2a) adapted to hold at least said two electric motors (4), elastic transmission system, output shaft (3) and control unit (9); finally, the holding structure (2) has: a driving output (3b) placed at the outer surface, which is controlled by the output shaft (3) and is adapted to set the movable component (102) in rotation about the rotation axis (3a), at least one stiff coupling element (5) adapted to enable a stiff connection of the holding structure (2), and a support output (2e) that is opposite to the driving output (3b) and substantially coaxial with the rotation axis (3a) and is adapted to partly house the movable component (102) stabilising the rotation of said movable component (102)
Overcoming the Torque/Stiffness Range Tradeoff in Antagonistic Variable Stiffness Actuators
No full textTo face the demand for applications in which robots have to safely interact with humans and the environment, the research community developed new types of actuators with compliant characteristics. To embody compliance into the actuator, elastic elements with fixed or variable compliance can be used. Among the variable stiffness mechanisms, a popular approach is based on the agonistic-antagonistic (A-A) layout, where two prime movers are elastically connected to the output shaft of the actuator. Notwithstanding the conceptually simple realization of the A-A layout, one limitation is that, due to the nonlinear torque/deflection characteristic of the elastic transmissions and to the limited spring elongation, the stiffness range achievable at the output shaft reduces as the external torque increases. In this work, a novel layout, based on the A-A principle, is proposed to increase the torque/stiffness capability of the actuator. To achieve this result, we combine elastic transmissions with linear and nonlinear torque/deflection characteristics. The mathematical model of the new layout and a possible implementation are analyzed. Then, the design of a novel variable stiffness actuator is presented and experimental validations are shown to compare the new device with the benchmark
A neuromuscular-model based control strategy to minimize muscle effort in assistive exoskeletons
No full textIn literature, much attention has been devoted to the design of control strategies of exoskeletons for assistive purposes. While several control schemes were presented, their performance still has limitations in minimizing muscle effort. According to this principle, we propose a novel approach to solve the problem of generating an assistive torque that minimizes muscle activation under stability guarantees. First, we perform a linear observability and controllability analysis of the human neuromuscular dynamic system. Based on the states that can be regulated with the available measurements and taking advantage of knowledge of the muscle model, we then solve an LQR problem in which a weighted sum of muscle activation and actuation torque is minimized to systematically synthesize a controller for an assistive exoskeleton.We evaluate the performance of the developed controller with a realistic non-linear human neuromusculoskeletal model. Simulation results show better performance in comparison with a well known controller in the literature, in the sense of closed loop system stability and regulation to zero of muscle effort
TraQuad: A Modular Tracked Legged Multimodal Quadrupedal Robot
No full textThe authors have developed a novel multimodal robot named TraQuad, which integrates the features of legged and tracked robots. This robot aims to combine agility, maneuverability, traction, and efficiency for traversing various environments. Legged locomotion allows the robot to select optimal contact points on the terrain, while tracked locomotion enables faster movement over relatively simpler uneven terrains with greater efficiency. TraQuad can turn about its central vertical axis and execute sharp turns with a 0.25 m turn radius. It can climb steep slopes of 31∘ at a velocity of 0.9 m/s. Utilizing multimodal locomotion, it can climb rocks and overcome obstacles by either skipping or stepping on them. Climbing rocks 1.75 times the height of the tracks requires a peak torque of 5.14 N⋅m, whereas stepping on a block of the same height requires a peak torque of 8.15 N⋅m. Skipping a block 1.5 times the height of tracks requires a peak torque of 11.8 N⋅m. This demonstrates that climbing obstacles while maintaining contact with them is more economical than stepping on them, proving the viability of tracked-legged locomotion. These advancements highlight the potential of TraQuad as a robust solution for navigating diverse and challenging environments
Optimal Control for Articulated Soft Robots
No full textSoft robots can execute tasks with safer interactions. However, control techniques that can effectively exploit the systems' capabilities are still missing. Differential dynamic programming (DDP) has emerged as a promising tool for achieving highly dynamic tasks. But most of the literature deals with applying the DDP to articulated soft robots by using numerical differentiation, in addition to using pure feed-forward control to perform explosive tasks. Further, underactuated compliant robots are known to be difficult to control and the use of DDP-based algorithms to control them is not yet addressed. We propose an efficient DDP-based algorithm for trajectory optimization of articulated soft robots that can optimize the state trajectory, input torques, and stiffness profile. We provide an efficient method to compute the forward dynamics and the analytical derivatives of series elastic actuators (SEA)/variable stiffness actuators (VSA) and underactuated compliant robots. We present a state-feedback controller that uses locally optimal feedback policies obtained from the DDP. We show through simulations and experiments that the use of feedback is crucial in improving the performance and stabilization properties of various tasks. We also show that the proposed method can be used to plan and control underactuated compliant robots with varying degrees of underactuation effectively
Grasping with Soft Hands
No full textDespite some prematurely optimistic claims, the ability of robots to grasp general objects in unstructured environments still remains far behind that of humans. This is not solely caused by differences in the mechanics of hands: indeed, we show that human use of a simple robot hand (the Pisa/IIT SoftHand) can afford capabilities that are comparable to natural grasping. It is through the observation of such human-directed robot hand operations that we realized how fundamental in everyday grasping and manipulation is the role of hand compliance, which is used to adapt to the shape of surrounding objects. Objects and environmental constraints are in turn used to functionally shape the hand, going beyond its nominal kinematic limits by exploiting structural softness. In this paper, we set out to study grasp planning for hands that are simple - in the sense of low number of actuated degrees of freedom (one for the Pisa/IIT SoftHand) - but are soft, i.e. continuously deformable in an infinity of possible shapes through interaction with objects. After general considerations on the change of paradigm in grasp planning that this setting brings about with respect to classical rigid multi-dof grasp planning, we present a procedure to extract grasp affordances for the Pisa/IIT SoftHand through physically accurate numerical simulations. The selected grasps are then successfully tested in an experimental scenario
SoftHandler: An Integrated Soft Robotic System for Handling Heterogeneous Objects
No full textThe picking performance of a robot can be severely affected by measurement errors, especially when handling objects that are fragile or irregular in shape and size. This is one of the main reasons that the problem of autonomously picking and placing objects is not solved. In this article, we exploit the “embodied” intelligence of soft robotic technologies to propose an integrated system, named SoftHandler, capable of overcoming some of the limitations of traditional pick-and-place industrial robots. The SoftHandler (Figure 1) integrates a novel parallel soft manipulator, the SoftDelta, and a novel soft end effector, the Pisa/(Istituto Italiano di Tecnologia) IIT SoftGripper
A robust iterative learning control for continuous-time nonlinear systems with disturbances
No full textIn this paper, we study the trajectory tracking problem using iterative learning control for continuous-time nonlinear systems with a generic fixed relative degree in the presence of disturbances. This class of controllers iteratively refine the control input relying on the tracking error of the previous trials and some properly tuned learning gains. Sufficient conditions on these gains guarantee the monotonic convergence of the iterative process. However, the choice of the gains is heuristically hand-tuned given an approximated system model and no information on the disturbances. Thus, in the cases of inaccurate knowledge of the model or iteration-varying measurement errors, external disturbances, and delays, the convergence condition is unlikely to be verified at every iteration. To overcome this issue, we propose a robust convergence condition, which ensures the applicability of the pure feedforward control even if other classical conditions are not fulfilled for some trials due to the presence of disturbances. Furthermore, we quantify the upper bound of the nonrepetitive disturbance that the iterative algorithm is able to handle. Finally, we validate the convergence condition simulating the dynamics of a two degrees of freedom underactuated arm with elastic joints, where one is active, and the other is passive, and a Franka Emika Panda manipulator
Dynamic morphological computation through damping design of soft material robots: application to under-actuated grippers
No full textThis article presents the design of soft material robots with tunable damping properties. This study derives from the investigation of an under-actuated dynamic approach involving multi-chamber pneumatic systems. The co-design of the mechanical parameters (stiffness and damping) of the system along with the time profile of the input allows to obtain different behaviors using a reduced number of feeding line. In this work we analyze via simulations and experiments several approaches to tune the damping of soft robots. The most effective solution employs a layer of granular material immersed in viscous oil within the chamber wall. This method has been employed to realize bending actuators with a continuous deformation pattern. Finally, we show an application involving a two-fingered gripper fed by a single pneumatic line, which is able to perform pinch and power grasp
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