10 citations · 19 across the 17 of their papers we have counts for
20 papers
ALFRED: Requirement-driven development of an open-source mobile manipulator for long-term plant monitoring
Ciarán Miceal Johnson, Christopher Quail, Garry Ellard +3
Tracking seasonal change in crops and forests requires observing the same plants repeatedly. Ground robots can do this at close range, and a manipulator gives their sensors more vi…
ContactKernels: Adaptive Proposals using Geometry-COnditioned Wrenches for Contact-Rich Manipulation
Aditya Kamireddypalli, Matías Mattamala, João Moura +3
Contact-rich insertion requires precise geometric alignment despite uncertainty in perception, geometry, and con- trol. When this uncertainty causes unintended contact, the re- sul…
Amortising Trajectory Optimisation for Residual MPC via Implicit Contact Differentiation
Daniel Layeghi, Thomas Corbères, Calum Arnott +4
Differentiable simulation can accelerate contact-rich trajectory optimisation by exposing local sensitivities of task outcomes to controls. Existing approaches either use finite di…
CASSR: Continuous A-Star Search through Reachability for real time footstep planning
Jiayi Wang, Steve Tonneau
Footstep planning involves a challenging combinatorial search. Traditional A* approaches require discretising reachability constraints, while Mixed-Integer Programming (MIP) suppor…
System Identification under Constraints and Disturbance: A Bayesian Estimation Approach
Sergi Martinez, Steve Tonneau, Carlos Mastalli
We introduce a Bayesian system identification (SysID) framework for jointly estimating robot's state trajectories and physical parameters with high accuracy. It embeds physically c…
Very High Frequency Interpolation for Direct Torque Control
Rafael Kourdis, Maciej Stępień, Jérôme Manhes +4
Torque control enables agile and robust robot motion, but deployment is often hindered by instability and hardware limits. Here, we present a novel solution to execute whole-body l…
Scaling Whole-body Multi-contact Manipulation with Contact Optimization
Victor Levé, João Moura, Sachiya Fujita +3
Daily tasks require us to use our whole body to manipulate objects, for instance when our hands are unavailable. We consider the issue of providing humanoid robots with the ability…
Explicit Contact Optimization in Whole-Body Contact-Rich Manipulation
Victor Leve, João Moura, Namiko Saito +2
Humans can exploit contacts anywhere on their body surface to manipulate large and heavy items, objects normally out of reach or multiple objects at once. However, such manipulatio…
NAS: N-step computation of All Solutions to the footstep planning problem
Jiayi Wang, Saeid Samadi, Hefan Wang +4
How many ways are there to climb a staircase in a given number of steps? Infinitely many, if we focus on the continuous aspect of the problem. A finite, possibly large number if we…
Online Multi-Contact Receding Horizon Planning via Value Function Approximation
Jiayi Wang, Sanghyun Kim, Teguh Santoso Lembono +8
Planning multi-contact motions in a receding horizon fashion requires a value function to guide the planning with respect to the future, e.g., building momentum to traverse large o…
Neural Lyapunov and Optimal Control
Daniel Layeghi, Steve Tonneau, Michael Mistry
Despite impressive results, reinforcement learning (RL) suffers from slow convergence and requires a large variety of tuning strategies. In this paper, we investigate the ability o…
Perceptive Locomotion through Whole-Body MPC and Optimal Region Selection
Thomas Corbères, Carlos Mastalli, Wolfgang Merkt +6
Real-time synthesis of legged locomotion maneuvers in challenging industrial settings is still an open problem, requiring simultaneous determination of footsteps locations several…
Topology-Based MPC for Automatic Footstep Placement and Contact Surface Selection
Jaehyun Shim, Carlos Mastalli, Thomas Corbères +3
State-of-the-art approaches to footstep planning assume reduced-order dynamics when solving the combinatorial problem of selecting contact surfaces in real time. However, in exchan…
Differentiable Optimal Control via Differential Dynamic Programming
Traiko Dinev, Carlos Mastalli, Vladimir Ivan +2
Robot design optimization, imitation learning and system identification share a common problem which requires optimization over robot or task parameters at the same time as optimiz…
Inverse-Dynamics MPC via Nullspace Resolution
Carlos Mastalli, Saroj Prasad Chhatoi, Thomas Corbères +2
Optimal control (OC) using inverse dynamics provides numerical benefits such as coarse optimization, cheaper computation of derivatives, and a high convergence rate. However, to ta…
Optimal Control via Combined Inference and Numerical Optimization
Daniel Layeghi, Steve Tonneau, Michael Mistry
Derivative based optimization methods are efficient at solving optimal control problems near local optima. However, their ability to converge halts when derivative information vani…
Convex strategies for trajectory optimisation: application to the Polytope Traversal Problem
Steve Tonneau
Non-linear Trajectory Optimisation (TO) methods require good initial guesses to converge to a locally optimal solution. A feasible guess can often be obtained by allocating a large…
A Versatile Co-Design Approach For Dynamic Legged Robots
Traiko Dinev, Carlos Mastalli, Vladimir Ivan +2
We present a versatile framework for the computational co-design of legged robots and dynamic maneuvers. Current state-of-the-art approaches are typically based on random sampling…
Solving Footstep Planning as a Feasibility Problem using L1-norm Minimization (Extended Version)
Daeun Song, Pierre Fernbach, Thomas Flayols +4
One challenge of legged locomotion on uneven terrains is to deal with both the discrete problem of selecting a contact surface for each footstep and the continuous problem of placi…
SL1M: Sparse L1-norm Minimization for contact planning on uneven terrain
Steve Tonneau, Daeun Song, Pierre Fernbach +3
One of the main challenges of planning legged locomotion in complex environments is the combinatorial contact selection problem. Recent contributions propose to use integer variabl…