23 accepted papers
Soft robots present unique challenges for accurate modeling and control due to their virtually infinite degrees of freedom and highly nonlinear deformations. High-fidelity continuum models offer accuracy but are often computationally prohibitive for real-time control, while purely learning-based pol…
Path Integral methods have demonstrated remarkable capabilities for solving non-linear stochastic optimal control problems through sampling-based optimization. However, their computational complexity grows linearly with the prediction horizon, limiting long-term reasoning, while constraints are mere
Path Integral methods have demonstrated remarkable capabilities for solving non-linear stochastic optimal control problems through sampling-based optimization. However, their computational complexity grows linearly with the prediction horizon, limiting long-term reasoning, while constraints are mere…
Designing robotic manipulators for generic tasks while meeting specific requirements is a complex, iterative process involving mechanical design, simulation, control, and testing. New computational design tools are needed to simplify and speed up such processes. This work presents an original formul
Ensuring constraint satisfaction is a key requirement for safety-critical systems, which include most robotic platforms. For example, constraints can be used for modeling joint position/velocity/torque limits and collision avoidance. Constrained systems are often controlled using Model Predictive Co
In recent years, advanced model-based and data-driven control methods are unlocking the potential of complex robotics systems, and we can expect this trend to continue at an exponential rate in the near future. However, ensuring safety with these advanced control methods remains a challenge. A well-…
This letter presents a novel algorithm for the continuous control of dynamical systems that combines Trajectory Optimization (TO) and Reinforcement Learning (RL) in a single framework. The motivations behind this algorithm are the two main limitations of TO and RL when applied to continuous nonlinea
Rescue missions in mountain environments are hardly achievable by standard legged robots—because of the high slopes—or by flying robots—because of limited payload capacity. We present a concept for a rope-aided climbing robot which can negotiate up-to-vertical slopes and carry heavy payloads. The ro…
Quadruped robots are machines intended for challenging and harsh environments. Despite the progress in locomotion strategy, safely recovering from unexpected falls or planned drops is still an open problem. It is further made more difficult when high horizontal velocities are involved. In this lette
This paper deals with the robust control of fully-actuated robots subject to joint position, velocity and acceleration bounds. Robotic systems are subject to disturbances, which may arise from modeling errors, sensor noises or communication delays. This work presents mathematical and computational t…
Safety is often the most important requirement in robotics applications. Nonetheless, control techniques that can provide safety guarantees are still extremely rare for nonlinear systems, such as robot manipulators. A well-known tool to ensure safety is the viability kernel, which is the largest set
This letter outlines a bi-level algorithm to concurrently optimize robot hardware and control parameters in order to minimize energy consumption during the execution of tasks and to ensure robust performance. The outer loop consists in a genetic algorithm that optimizes the co-design variables accor
Extended version of the paper to be published in IEEE Robotics and Automation Letters
Versatility is one of the main factors driving the adoption of robots on the assembly line and in other applications. Compared to fixed-automation solutions, a single industrial robot can perform a wide range of tasks (e.g., welding, lifting). In other platforms, such as legged robots, versatility i
One of the main challenges of planning legged locomotion in complex environments is the combinatorial contact selection problem. Recent contributions propose to use integer variables to represent which contact surface is selected, and then to rely on modern mixed-integer (MI) optimization solvers to…
This letter deals with the problem of controlling a robotic system whose joints have bounded position, velocity, and acceleration/torque. Assuming a discrete-time acceleration control, we compute tight bounds on the current joint accelerations that ensure the existence of a feasible trajectory in th
Recently, the centroidal momentum dynamics has received substantial attention to plan dynamically consistent motions for robots with arms and legs in multi-contact scenarios. However, it is also non convex which renders any optimization approach difficult and timing is usually kept fixed in most tra…
We present a novel method for synthesizing collision-free, dynamic locomotion behaviors for legged robots, including jumping, going down a very steep slope, or recovering from a push using the arms of the robot. The approach is automatic and generic: non-gaited motions, comprising arbitrary contact…
The identification of inertial parameters is crucial to achieve high-performance model-based control of legged robots. The inertial parameters of the legs are typically not altered during expeditions and therefore are best identified offline. On the other hand, the trunk parameters depend on the mod…
Maintaining equilibrium is of primary importance for legged systems. It is not surprising then that static equilibrium is at the core of most control/planning algorithms for legged robots. Being able to check whether a system is in static equilibrium is thus important, and doing it efficiently is cr
Task-Space Inverse Dynamics (TSID) is a well-known optimization-based technique for the control of highly-redundant mechanical systems, such as humanoid robots. One of its main flaws is that it does not take into account any of the uncertainties affecting these systems: poor torque tracking, sensor…
Classically robot force control passes through joint torques measurement or estimation. Within this context, classical torque sensing technologies rely on current sensing on motor windings and on torsion sensing on motor shaft. An alternative approach was recently proposed in [1] and combines whole-…
This paper deals with the generation of motion for complex dynamical systems (such as humanoid robots) to achieve several concurrent objectives. Hierarchy of tasks and optimal control are two frameworks commonly used to this aim. The first one specifies control objectives as a number of quadratic fu…