5 papers
Constraint-Aware Reinforcement Learning via Adaptive Action Scaling
Murad Dawood, Usama Ahmed Siddiquie, Shahram Khorshidi +1
Safe reinforcement learning (RL) seeks to mitigate unsafe behaviors that arise from exploration during training by reducing constraint violations while maintaining task performance…
DogLegs: Robust Proprioceptive State Estimation for Legged Robots Using Multiple Leg-Mounted IMUs
Yibin Wu, Jian Kuang, Shahram Khorshidi +4
Robust and accurate proprioceptive state estimation of the main body is crucial for legged robots to execute tasks in extreme environments where exteroceptive sensors, such as LiDA…
End-to-End Multi-Task Policy Learning from NMPC for Quadruped Locomotion
Anudeep Sajja, Shahram Khorshidi, Sebastian Houben +1
Quadruped robots excel in traversing complex, unstructured environments where wheeled robots often fail. However, enabling efficient and adaptable locomotion remains challenging du…
Physically-Consistent Parameter Identification of Robots in Contact
Shahram Khorshidi, Murad Dawood, Benno Nederkorn +2
Accurate inertial parameter identification is crucial for the simulation and control of robots encountering intermittent contact with the environment. Classically, robots' inertial…
Centroidal State Estimation based on the Koopman Embedding for Dynamic Legged Locomotion
Shahram Khorshidi, Murad Dawood, Maren Bennewitz
In this paper, we introduce a novel approach to centroidal state estimation, which plays a crucial role in predictive model-based control strategies for dynamic legged locomotion.…