Reconfigurable Hydrostatics: Toward Multifunctional and Powerful Wearable Robotics

Wearable and locomotive robot designers face multiple challenges when choosing actuation. Traditional fully actuated designs using electric motors are multifunctional but oversized and inefficient for bearing conservative loads and for being backdrivable. Alternatively, quasi-passive and underactuated designs reduce the size of motorization and energy storage, but are often designed for specific tasks. Designers of versatile and stronger wearable robots will face these challenges unless future actuators become very torque-dense, backdrivable and efficient. This paper explores a design paradigm for addressing this issue: reconfigurable hydrostatics. We show that a hydrostatic actuator can integrate a passive force mechanism and a sharing mechanism in the fluid domain and still be multifunctional. First, an analytical study compares how these two mechanisms can relax the motorization requirements in the context of a load-bearing exoskeleton. Then, the hydrostatic concept integrating these two mechanisms using hydraulic components is presented. A case study analysis shows the mass/efficiency/inertia benefits of the concept over a fully actuated one. Then, the feasibility of the concept is partially validated with a proof-of-concept that actuates the knees of an exoskeleton. The experiments show that it can track the vertical ground reaction force (GRF) profiles of walking, running, squatting, and jumping, and that the energy consumption is 6x lower. The transient force behaviors due to switching from one leg to the other are also analyzed along with some mitigation to improve them.

Influence Vectors Control for Robots Using Cellular-like Binary Actuators

Robots using cellular-like redundant binary actuators could outmatch electric-gearmotor robotic systems in terms of reliability, force-to-weight ratio and cost. This paper presents a robust fault tolerant control scheme that is designed to meet the control challenges encountered by such robots, i.e., discrete actuator inputs, complex system modeling and cross-coupling between actuators. In the proposed scheme, a desired vectorial system output, such as a position or a force, is commanded by recruiting actuators based on their influence vectors on the output. No analytical model of the system is needed; influence vectors are identified experimentally by sequentially activating each actuator. For position control tasks, the controller uses a probabilistic approach and a genetic algorithm to determine an optimal combination of actuators to recruit. For motion control tasks, the controller uses a sliding mode approach and independent recruiting decision for each actuator. Experimental results on a four degrees of freedom binary manipulator with twenty actuators confirm the method's effectiveness, and its ability to tolerate massive perturbations and numerous actuator failures.

Soft Two-degree-of-freedom Dielectric Elastomer Position Sensor Exhibiting Linear Behavior

Soft robots could bring robotic systems to new horizons, by enabling safe human-machine interaction. For precise control, these soft structures require high level position feedback that is not easily achieved through conventional one-degree-of-freedom (DOF) sensing apparatus. In this paper, a soft two-DOF dielectric elastomer (DE) sensor is specifically designed to provide accurate position feedback for a soft polymer robotic manipulator. The technology is exemplified on a soft robot intended for MRI-guided prostate interventions. DEs are chosen for their major advantages of softness, high strains, low cost and embedded multiple-DOF sensing capability, providing excellent system integration. A geometrical model of the proposed DE sensor is developed and compared to experimental results in order to understand sensor mechanics. Using a differential measurement approach, a handmade prototype provided linear sensory behavior and 0.2 mm accuracy on two-DOF. This correlates to a 0.7\% error over the sensor's 30 mm x 30 mm planar range, demonstrating the outstanding potential of DE technology for accurate multi-DOF position sensing.

A two-speed actuator for robotics with fast seamless gear shifting

This paper present a novel dual-speed actuator adapted to robotics. In many applications, robots have to bear large loads while moving slowly and also have to move quickly through the air with almost no load. This lead to conflicting requirements for their actuators. Multiple gear ratios address this issue by allowing an effective use of power over a wide range of torque-speed load conditions. Furthermore, very different gear ratios also lead to drastic changes of the intrinsic impedance, enabling a non-back-drivable mode for stiff position control and a back-drivable mode for force control. The proposed actuator consists of two electric motors coupled to a differential; one has a large gear ratio while the other is almost direct-drive and equipped with a brake. During the high-force mode the brake is locked, only one motor is used, and the actuator behaves like a regular highly-geared servo-motor. During the high-speed mode the brake is open, both motor are used at the same time, and the actuator behaves like a direct drive motor. A dynamic model is developed and novel controllers are proposed for synergic use of both motors. The redundancy of motors is exploited for maintaining full control of the output during mode transitions, allowing for fast and seamless switching even when interacting with unknown environments. Results are demonstrated with a proof-of-concept linear actuator.

Leveraging Natural Load Dynamics with Variable Gear-ratio Actuators

This paper presents a robotic system where the gear-ratio of an actuator is dynamically changed to either leverage or attenuate the natural load dynamics. Based on this principle, lightweight robotic systems can be made fast and strong; exploiting the natural load dynamics for moving at higher speeds (small reduction ratio), while also able to bear a large load through the attenuation of the load dynamics (large reduction ratio). A model-based control algorithm to automatically select the optimal gear-ratios that minimize the total actuator torques for an arbitrary dynamic state and expected uncertainty level is proposed. Also, a novel 3-DoF robot arm using custom actuators with two discrete gear-ratios is presented. The advantages of gear-shifting dynamically are demonstrated through experiments and simulations. Results show that actively changing the gear-ratio using the proposed control algorithms can lead to an order-of-magnitude reduction of necessary actuator torque and power, and also increase robustness to disturbances.

A Dual-Motor Actuator for Ceiling Robots with High Force and High Speed Capabilities

Patient transfer devices allow to move patients passively in hospitals and care centers. Instead of hoisting the patient, it would be beneficial in some cases to assist their movement, enabling them to move by themselves. However, patient assistance requires devices capable of precisely controlling output forces at significantly higher speeds than those used for patient transfers alone, and a single motor solution would be over-sized and show poor efficiency to do both functions. This paper presents a dual-motor actuator and control schemes adapted for a patient mobility equipment that can be used to transfer patients, assist patient in their movement, and help prevent falls. The prototype is shown to be able to lift patients weighing up to 318 kg, to assist a patient with a desired force of up to 100 kg with a precision of 7.8%. Also, a smart control scheme to manage falls is shown to be able to stop a patient who is falling by applying a desired deceleration.

Using Buckingham's $π$ Theorem for Multi-System Learning Transfer: a Case-study with 3 Vehicles Sharing a Database

Learning schemes for planning and control are limited by the difficulty of collecting large amounts of experimental data or having to rely on high-fidelity simulations. This paper explores the potential of a proposed learning scheme that leverages dimensionless numbers based on Buckingham's $\pi$ theorem to improve data efficiency and facilitate knowledge sharing between similar systems. A case study using car-like robots compares traditional and dimensionless learning models on simulated and experimental data to validate the benefits of the new dimensionless learning approach. Preliminary results show that this new dimensionless approach could accelerate the learning rate and improve the accuracy of the model and should be investigated further.

Assessing Wind Impact on Semi-Autonomous Drone Landings for In-Contact Power Line Inspection

In recent years, the use of inspection drones has become increasingly popular for high-voltage electric cable inspections due to their efficiency, cost-effectiveness, and ability to access hard-to-reach areas. However, safely landing drones on power lines, especially under windy conditions, remains a significant challenge. This study introduces a semi-autonomous control scheme for landing on an electrical line with the NADILE drone (an experimental drone based on original LineDrone key features for inspection of power lines) and assesses the operating envelope under various wind conditions. A Monte Carlo method is employed to analyze the success probability of landing given initial drone states. The performance of the system is evaluated for two landing strategies, variously controllers parameters and four level of wind intensities. The results show that a two-stage landing strategies offers higher probabilities of landing success and give insight regarding the best controller parameters and the maximum wind level for which the system is robust. Lastly, an experimental demonstration of the system landing autonomously on a power line is presented.

Dimensionless Policies based on the Buckingham $π$ Theorem: Is it a good way to Generalize Numerical Results?

Yes if the context, the list of variables defining the motion control problem, is dimensionally similar. Here we show that by modifying the problem formulation using dimensionless variables, we can re-use the optimal control law generated numerically for a specific system to a sub-space of dimensionally similar systems. This is demonstrated, with numerically generated optimal controllers, for the classic motion control problem of swinging-up a torque-limited inverted pendulum. We also discuss the concept of regime, a region in the space of context variables, that can help relax the condition on dimensional similarity. Futhermore, we discuss how applying dimensionnal scaling of the input and output of a context-specific policy is equivalent to substituing the new systems parameters in an analytical equation for dimentionnaly similar systems. It remains to be seen if this approach can also help generalizing policies for more complex high-dimensional problems.

A Bimodal Hydrostatic Actuator for Robotic Legs with Compliant Fast Motion and High Lifting Force

Robotic legs have bimodal operations: swing phases when the leg needs to move quickly in the air (high-speed, low-force) and stance phases when the leg bears the weight of the system (low-speed, high-force). Sizing a traditional single-ratio actuation system for such extremum operations leads to oversized heavy electric motor and poor energy efficiency, which hinder the capability of legged systems that bear the mass of their actuators and energy source. This paper explores an actuation concept where a hydrostatic transmission is dynamically reconfigured using valves to suit the requirements of each phase of a robotic leg. An analysis of the mass-delay-flow trade-off for the switching valve is presented. Then, a custom actuation system is built and integrated on a robotic leg test bench to evaluate the concept. Experimental results show that 1) small motorized ball valves can make fast transitions between operating modes when designed for this task, 2) the proposed operating principle and control schemes allow for seamless transitions, even during an impact with the ground and 3) the actuator characteristics address the needs of a leg bimodal operation in terms of force, speed and compliance.