8 accepted papers
Drifting, characterized by controlled vehicle motion at high sideslip angles, is crucial for safely handling emergency scenarios at the friction limits. While recent reinforcement learning approaches show promise for drifting control, they struggle with the significant simulation-to-reality gap, as …
This paper presents a hierarchical control framework for quadrupedal locomotion that unifies the complementary strengths of model-based optimization and reinforcement learning. We develop a convex Quadratic Programming~(QP) solver based on the primal-dual Chambolle-Pock algorithm, enabling both mass…
Autonomous post-fall recovery is a key bottleneck for long-duration deployment of legged robots, yet prevailing methods depend on flat-ground target poses and heuristic rewards and thus fail to generalize under irregular terrain and random initial states. We introduce a teacher-guided, terrain-aware
In this paper, we propose a differential-flatness-based controller (DFBC) for precise trajectory tracking of tractor-trailers, particularly during reversing maneuvers, which are challenging due to unstable equilibrium points. The proposed controller leverages the differential flatness property of tr
Wheeled-legged robots combine the efficiency of wheels with the versatility of legs, but face significant energy optimization challenges when navigating diverse environments. In this work, we present a hierarchical control framework that integrates predictive power modeling with residual reinforceme
Drifting, characterized by controlled vehicle motion at high sideslip angles, is crucial for safely handling emergency scenarios at the friction limits. While recent reinforcement learning approaches show promise for drifting control, they struggle with the significant simulation-to-reality gap, as
Inertia drift is an aggressive transitional driving maneuver, which is challenging due to the high nonlinearity of the system and the stringent requirement on control and planning performance. This paper presents a solution for the consecutive inertia drift of an autonomous RC car based on primitive…
Maneuvering an autonomous vehicle under drift condition is critical to the safety of autonomous vehicles when there is a sudden loss of traction due to external conditions such as rain or snow, which is a challenging control problem due to the presence of significant sideslip and nearly full saturat…