Constrained Annealing-based Sampling MPC (CAS-MPC), which integrates inequality constraints via a primal–dual weight reshaping scheme that preserves sample diversity, and a hybrid refinement strategy that switches to Sequential Linear–Quadratic MPC for millimeter-level precision once near the goal is proposed.
Safe robot control often requires combining long-horizon performance optimization with hard state and input constraints, but existing approaches tend to address this tradeoff partially. Sampling-based model predictive control (MPC) methods such as model predictive path integral (MPPI) are effective in handling nonlinea...
A. Didier, J. Choi, Namhoon Cho et al.· 0 citations
Bimanual manipulation in cluttered, contact-rich environments remains challenging because it requires coordinated motion generation, interaction-aware planning, and reliable execution under tight kinematic constraints. We present PRISM, a projection-integrated sampling-based Model Predictive Control (MPC) framework tha...
A. Dan, Iryna Hurova, Karl Kruusamäe et al.· 0 citations
Shape-Aware Reinforcement Learned Model Predictive Control is proposed, a method for safe, efficient, and adaptive navigation in crowds with heterogeneous shapes without geometry simplification that preserves the safety structure and generalizability of MPC while integrating the adaptability and intelligence of RL.
Contact-implicit trajectory optimization formulates contact-rich manipulation as a single constrained program; however, that single program run collapses onto one local optimum out of many equally valid contact modes, grasps, or push directions. As a consequence, the resulting manipulation strategy is reluctant to chan...
Hrishikesh Sathyanarayan, Christian Hughes, Ian Abraham· 0 citations
This work identifies a structural failure mode of this method class on terminal-navigation tasks: reaching a precise goal configuration while satisfying safety constraints that tighten along the final approach, and empirically demonstrates that adding a dense per-step success signal via an auxiliary value critic improv...
Aman Arora, Ricard M. Castan, Matteo El-Hariry et al.· 0 citations
Humanoid locomotion in highly confined environments requires navigating dense environmental obstacles and complex self-collision bounds while maintaining multi-contact dynamic feasibility. Traditional trajectory optimizers frequently struggle in these restricted spaces, as navigating the large collision space with spli...
Carlos Gonzalez, Luis Sentis· 0 citations
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