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Vision-Language-Policy Model for Dynamic Robot Task Planning
Jin Wang, Kim Tien Ly, Jacques Cloete +3
Bridging the gap between natural language commands and autonomous execution in unstructured environments remains an open challenge for robotics. This requires robots to perceive an…
Sampling Strategies for Robust Universal Quadrupedal Locomotion Policies
David Rytz, Kim Tien Ly, Ioannis Havoutis
This work focuses on sampling strategies of configuration variations for generating robust universal locomotion policies for quadrupedal robots. We investigate the effects of sampl…
RAKOMO: Reachability-Aware K-Order Markov Path Optimization for Quadrupedal Loco-Manipulation
Mattia Risiglione, Abdelrahman Abdalla, Victor Barasuol +3
Legged manipulators, such as quadrupeds equipped with robotic arms, require motion planning techniques that account for their complex kinematic constraints in order to perform mani…
InteLiPlan: An Interactive Lightweight LLM-Based Planner for Domestic Robot Autonomy
Kim Tien Ly, Kai Lu, Ioannis Havoutis
We introduce an interactive LLM-based framework designed to enhance the autonomy and robustness of domestic robots, targeting embodied intelligence. Our approach reduces reliance o…
Adaptive Manipulation using Behavior Trees
Jacques Cloete, Wolfgang Merkt, Ioannis Havoutis
Many manipulation tasks pose a challenge since they depend on non-visual environmental information that can only be determined after sustained physical interaction has already begu…
Gaitor: Learning a Unified Representation Across Gaits for Real-World Quadruped Locomotion
Alexander L. Mitchell, Wolfgang Merkt, Aristotelis Papatheodorou +2
The current state-of-the-art in quadruped locomotion is able to produce a variety of complex motions. These methods either rely on switching between a discrete set of skills or lea…
Momentum-Aware Trajectory Optimisation using Full-Centroidal Dynamics and Implicit Inverse Kinematics
Aristotelis Papatheodorou, Wolfgang Merkt, Alexander L. Mitchell +1
The current state-of-the-art gradient-based optimisation frameworks are able to produce impressive dynamic manoeuvres such as linear and rotational jumps. However, these methods, w…
R-LGP: A Reachability-guided Logic-geometric Programming Framework for Optimal Task and Motion Planning on Mobile Manipulators
Kim Tien Ly, Valeriy Semenov, Mattia Risiglione +2
This paper presents an optimization-based solution to task and motion planning (TAMP) on mobile manipulators. Logic-geometric programming (LGP) has shown promising capabilities for…