arXiv subjects

Alexandre Girard

Publications and source records attributed to Alexandre Girard.

At least 19 recordsLinked to original sources

arXiv2025

A Two Degrees-of-Freedom Floor-Based Robot for Transfer and Rehabilitation Applications

The ability to accomplish a sit-to-stand (STS) motion is key to increase functional mobility and reduce rehospitalization risks. While raising aid (transfer) devices and partial bodyweight support (rehabilitation) devices exist, both are unable to adjust the STS training to different mobility levels. Therefore, We have developed an STS training device that allows various configurations of impedance and vertical/forward forces to adapt to many training needs while maintaining commercial raising aid transfer capabilities. Experiments with healthy adults (both men and women) of various heights and weights show that the device 1) has a low impact on the natural STS kinematics, 2) can provide precise weight unloading at the patient's center of mass and 3) can add a forward virtual spring to assist the transfer of the bodyweight to the feet for seat-off, at the start of the STS motion.

cs.RO↗

arXiv2025

Theoretical Closed-loop Stability Bounds for Dynamical System Coupled with Diffusion Policies

Diffusion Policy has shown great performance in robotic manipulation tasks under stochastic perturbations, due to its ability to model multimodal action distributions. Nonetheless, its reliance on a computationally expensive reverse-time diffusion (denoising) process, for action inference, makes it challenging to use for real-time applications where quick decision-making is mandatory. This work studies the possibility of conducting the denoising process only partially before executing an action, allowing the plant to evolve according to its dynamics in parallel to the reverse-time diffusion dynamics ongoing on the computer. In a classical diffusion policy setting, the plant dynamics are usually slow and the two dynamical processes are uncoupled. Here, we investigate theoretical bounds on the stability of closed-loop systems using diffusion policies when the plant dynamics and the denoising dynamics are coupled. The contribution of this work gives a framework for faster imitation learning and a metric that yields if a controller will be stable based on the variance of the demonstrations.

cs.RO↗

arXiv2025

Zero-Shot Policy Transfer in Reinforcement Learning using Buckingham's Pi Theorem

Reinforcement learning (RL) policies often fail to generalize to new robots, tasks, or environments with different physical parameters, a challenge that limits their real-world applicability. This paper presents a simple, zero-shot transfer method based on Buckingham's Pi Theorem to address this limitation. The method adapts a pre-trained policy to new system contexts by scaling its inputs (observations) and outputs (actions) through a dimensionless space, requiring no retraining. The approach is evaluated against a naive transfer baseline across three environments of increasing complexity: a simulated pendulum, a physical pendulum for sim-to-real validation, and the high-dimensional HalfCheetah. Results demonstrate that the scaled transfer exhibits no loss of performance on dynamically similar contexts. Furthermore, on non-similar contexts, the scaled policy consistently outperforms the naive transfer, significantly expanding the volume of contexts where the original policy remains effective. These findings demonstrate that dimensional analysis provides a powerful and practical tool to enhance the robustness and generalization of RL policies.

cs.LG↗

arXiv2025

Model-Based Real-Time Pose and Sag Estimation of Overhead Power Lines Using LiDAR for Drone Inspection

Drones can inspect overhead power lines while they remain energized, significantly simplifying the inspection process. However, localizing a drone relative to all conductors using an onboard LiDAR sensor presents several challenges: (1) conductors provide minimal surface for LiDAR beams limiting the number of conductor points in a scan, (2) not all conductors are consistently detected, and (3) distinguishing LiDAR points corresponding to conductors from other objects, such as trees and pylons, is difficult. This paper proposes an estimation approach that minimizes the error between LiDAR measurements and a single geometric model representing the entire conductor array, rather than tracking individual conductors separately. Experimental results, using data from a power line drone inspection, demonstrate that this method achieves accurate tracking, with a solver converging under 50 ms per frame, even in the presence of partial observations, noise, and outliers. A sensitivity analysis shows that the estimation approach can tolerate up to twice as many outlier points as valid conductors measurements.

cs.RO↗

arXiv2024

Reconfigurable hydrostatics: Toward versatile and efficient load-bearing robotics

Wearable and legged 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 amount 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 the effect of these two mechanisms on 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, experiments are conducted on robotic legs to demonstrate that the actuator concept can meet the expected performance in terms of force tracking, versatility, and efficiency under controlled conditions. The proof-of-concept can track the vertical ground reaction force (GRF) profiles of walking, running, squatting, and jumping, and the energy consumption is 4.8x lower for walking. The transient force behaviors due to switching from one leg to the other are also analyzed along with some mitigation to improve them.

cs.RO↗

arXiv2024

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.

cs.RO↗

arXiv2024

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.

cs.RO↗

arXiv2024

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.

cs.RO↗

arXiv2024

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.

cs.RO↗

arXiv2024

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.

cs.RO↗

arXiv2023

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

Many advanced driver assistance schemes or autonomous vehicle controllers are based on a motion model of the vehicle behavior, i.e., a function predicting how the vehicle will react to a given control input. Data-driven models, based on experimental or simulated data, are very useful, especially for vehicles difficult to model analytically, for instance, ground vehicles for which the ground-tire interaction is hard to model from first principles. However, learning schemes 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 an approach that uses dimensionless numbers based on Buckingham's $\pi$ theorem to improve the efficiency of data for learning models, with the goal of facilitating knowledge sharing between similar systems. A case study using car-like vehicles compares traditional and dimensionless models on simulated and experimental data to validate the benefits of the new dimensionless learning approach. Prediction accuracy improvements with the dimensionless scheme when using a shared database, that is, predicting the motion of a vehicle based on data from various different vehicles was found to be 480\% more accurate for predicting a simple no-slip maneuver based on simulated data and 11\% more accurate to predict a highly dynamic braking maneuver based on experimental data. A modified physics-informed learning scheme with hand-crafted dimensionless features was also shown to increase the improvement to precision gains of 917\% and 28\% respectively. A comparative study also shows that using Buckingham's $\pi$ theorem is a much more effective preprocessing step for this task than principal component analysis (PCA) or simply normalizing the data.

cs.RO↗

arXiv2023

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.

eess.SY↗

arXiv2023

Dimensionless Policies based on the Buckingham $\pi$ Theorem: Is This a Good Way to Generalize Numerical Results?

The answer to the question posed in the title is yes if the context (the list of variables defining the motion control problem) is dimensionally similar. This article explores the use of the Buckingham $\pi$ theorem as a tool to encode the control policies of physical systems into a more generic form of knowledge that can be reused in various situations. This approach can be interpreted as enforcing invariance to the scaling of the fundamental units in an algorithm learning a control policy. First, we show, by restating the solution to a motion control problem using dimensionless variables, that (1) the policy mapping involves a reduced number of parameters and (2) control policies generated numerically for a specific system can be transferred exactly to a subset of dimensionally similar systems by scaling the input and output variables appropriately. Those two generic theoretical results are then demonstrated, with numerically generated optimal controllers, for the classic motion control problem of swinging up a torque-limited inverted pendulum and positioning a vehicle in slippery conditions. We also discuss the concept of regime, a region in the space of context variables, that can help to relax the similarity condition. Furthermore, we discuss how applying dimensional scaling of the input and output of a context-specific black-box policy is equivalent to substituting new system parameters in an analytical equation under some conditions, using a linear quadratic regulator (LQR) and a computed torque controller as examples. It remains to be seen how practical this approach can be to generalize policies for more complex high-dimensional problems, but the early results show that it is a promising transfer learning tool for numerical approaches like dynamic programming and reinforcement learning.

math.OC↗

arXiv2022

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.

cs.RO↗

arXiv2022

Multimodal Hydrostatic Actuators for Wearable Robots: A Preliminary Assessment of Mass-Saving and Energy-Efficiency Opportunities

Wearable robots are limited by their actuators performances because they must bear the weight of their own power system and energy source. This paper explores the idea of leveraging hybrid modes to meet multiple operating points with a lightweight and efficient system by using hydraulic valves to dynamically reconfigure the connections of a hydrostatic actuator. The analyzed opportunities consist in 1) switching between a highly geared power source or a fast power source, 2) dynamically connecting an energy accumulator and 3) using a locking mechanism for holding. Based on a knee exoskeleton case study analysis, results show that switching between gearing ratio can lead to a lighter and more efficient actuator. Also, results show that using an accumulator to provide a preload continuous force has great mass-saving potential, but does not reduce mass significantly if used as a power booster for short transients. Finally, using a locking valve can slightly reduce battery mass if the work cycle includes frequent stops. The operating principles of the proposed multimodal schemes are demonstrated with a one-DOF prototype.

cs.RO↗

arXiv2022

Low-Level Force-Control of MR-Hydrostatic Actuators

Precise and high-fidelity force control is critical for new generations of robots that interact with humans and unknown environments. Mobile robots, such as wearable devices and legged robots, must also be lightweight to accomplish their function. Hydrostatic transmissions have been proposed as a promising strategy for meeting these two challenging requirements. In previous publications, it was shown that using magnetorheological (MR) actuators coupled with hydrostatic transmissions provides high power density and great open-loop human-robot interactions. Still, the open-loop force fidelity at low and high frequencies are decreased by the transmission's dynamics and by nonlinear friction. This letter compares control strategies for MR-hydrostatic actuator systems to increase its torque fidelity, defined as the bandwidth (measured vs desired torque reference) and transparency (minimizing the undesired forces reflected to the end effector when backdriving the robot). Four control approaches are developed and compared experimentally: (1) Open-loop control with friction compensation; (2) non-collocated pressure feedback; (3) collocated pressure feedback; (4) LQGI state feedback. A dither strategy is also implemented to smoothen ball screw friction. Results show that approaches (1), (2) and (3) can increase the performances but are facing compromises, while approach (4) can simultaneously improve all metrics. These results show the potential of using control schemes for improving the force control performance of robots using tethered architectures, addressing issues such as transmission dynamics and friction.

cs.RO↗

arXiv2022

A Lightweight Force-Controllable Wearable Arm Based on Magnetorheological-Hydrostatic Actuators

Supernumerary Robotic Limbs (SRLs) are wearable robots augmenting human capabilities by acting as a co-worker, reaching objects, support human arms, etc. However, existing SRLs lack the mechanical backdrivability and bandwidth required for tasks where the interaction forces must be controllable such as painting, manipulating fragile objects, etc. Being highly backdrivable with a high bandwidth while minimizing weight presents a major technological challenge imposed by the limited performances of conventional electromagnetic actuators. This paper studies the feasibility of using magnetorheological (MR) clutches coupled to a low-friction hydrostatic transmission to provide a highly capable, but yet lightweight, force-controllable SRL. A 2.7 kg 2-DOFs wearable robotic arm is designed and built. Shoulder and elbow joints are designed to deliver 39 and 25 Nm, with 115 and 180{\deg} of range of motion. Experimental studies conducted on a one-DOF test bench and validated analytically demonstrate a high force bandwidth (>25 Hz) and a good ability to control interaction forces even when interacting with an external impedance. Furthermore, three force-control approaches are studied and demonstrated experimentally: open-loop, closed-loop on force, and closed-loop on pressure. All three methods are shown to be effective. Overall, the proposed MR-Hydrostatic actuation system is well-suited for a lightweight SRL interacting with both human and environment that add unpredictable disturbances.

cs.RO↗

arXiv2022

Performance Study of Low Inertia Magnetorheological Actuators for Kinesthetic Haptic Devices

A challenge to high quality virtual reality (VR) simulations is the development of high-fidelity haptic devices that can render a wide range of impedances at both low and high frequencies. To this end, a thorough analytical and experimental assessment of the performance of magnetorheological (MR) actuators is performed and compared to electric motor (EM) actuation. A 2 degrees-of-freedom dynamic model of a kinesthetic haptic device is used to conduct the analytical study comparing the rendering area, rendering bandwidth, gearing and scaling of both technologies. Simulation predictions are corroborated by experimental validation over a wide range of operating conditions. Results show that, for a same output force, MR actuators can render a bandwidth over 52.9% higher than electric motors due to their low inertia. Unlike electric motors, the performance of MR actuators for use in haptic devices are not limited by their output inertia but by their viscous damping, which must be carefully addressed at the design stage.

cs.RO↗