Publications (7)
Trajectory Generation for Quadrotor Based Systems using Numerical Optimal Control
Mathieu Geisert, Nicolas Mansard
The recent works on quadrotor have focused on more and more challenging tasks on increasingly complex systems. Systems are often augmented with slung loads, inverted pendulums or a…
Next Steps: Learning a Disentangled Gait Representation for Versatile Quadruped Locomotion
Alexander L. Mitchell, Wolfgang Merkt, Mathieu Geisert +5
Quadruped locomotion is rapidly maturing to a degree where robots now routinely traverse a variety of unstructured terrains. However, while gaits can be varied typically by selecti…
RLOC: Terrain-Aware Legged Locomotion using Reinforcement Learning and Optimal Control
Siddhant Gangapurwala, Mathieu Geisert, Romeo Orsolino +2
We present a unified model-based and data-driven approach for quadrupedal planning and control to achieve dynamic locomotion over uneven terrain. We utilize on-board proprioceptive…
VAE-Loco: Versatile Quadruped Locomotion by Learning a Disentangled Gait Representation
Alexander L. Mitchell, Wolfgang Merkt, Mathieu Geisert +5
Quadruped locomotion is rapidly maturing to a degree where robots are able to realise highly dynamic manoeuvres. However, current planners are unable to vary key gait parameters of…
Contact Planning for the ANYmal Quadruped Robot using an Acyclic Reachability-Based Planner
Mathieu Geisert, Thomas Yates, Asil Orgen +2
Despite the great progress in quadrupedal robotics during the last decade, selecting good contacts (footholds) in highly uneven and cluttered environments still remains an open cha…
Receding-Horizon Perceptive Trajectory Optimization for Dynamic Legged Locomotion with Learned Initialization
Oliwier Melon, Romeo Orsolino, David Surovik +3
To dynamically traverse challenging terrain, legged robots need to continually perceive and reason about upcoming features, adjust the locations and timings of future footfalls and…