Differential Flatness Transformations for Aggressive Quadrotor Flight. - Benjamin Morrell; Marc Rigter; Gene Merewether; Robert Reid 001; Rohan Thakker; Theodore Tzanetos; Vinay Rajur; Gregory E. Chamitoff (ICRA, 2018)

Comparison of Trajectory Optimization Algorithms for High-Speed Quadrotor Flight Near Obstacles. - Benjamin Morrell; Rohan Thakker; Gene Merewether; Robert Reid 001; Marc Rigter; Theodore Tzanetos; Gregory E. Chamitoff (IEEE Robotics Autom. Lett., 2018)

Robot Path Planning for Multiple Target Regions. - Shu Ishida; Marc Rigter; Nick Hawes (ECMR, 2019)

An Autonomous Quadrotor System for Robust High-Speed Flight Through Cluttered Environments Without GPS. - Marc Rigter; Benjamin Morrell; Robert G. Reid; Gene B. Merewether; Theodore Tzanetos; Vinay Rajur; K. C. Wong 001; Larry H. Matthies (IROS, 2019)

A Framework for Learning From Demonstration With Minimal Human Effort. - Marc Rigter; Bruno Lacerda; Nick Hawes (IEEE Robotics Autom. Lett., 2020)

Minimax Regret Optimisation for Robust Planning in Uncertain Markov Decision Processes. - Marc Rigter; Bruno Lacerda; Nick Hawes (AAAI, 2021)

Risk-Averse Bayes-Adaptive Reinforcement Learning. - Marc Rigter; Bruno Lacerda; Nick Hawes (NeurIPS, 2021)

Lexicographic Optimisation of Conditional Value at Risk and Expected Value for Risk-Averse Planning in MDPs. - Marc Rigter; Paul Duckworth; Bruno Lacerda; Nick Hawes (CoRR, 2021)

Optimal Admission Control for Multiclass Queues with Time-Varying Arrival Rates via State Abstraction. - Marc Rigter; Danial Dervovic; Parisa Hassanzadeh; Jason Long; Parisa Zehtabi; Daniele Magazzeni (AAAI, 2022)

Planning for Risk-Aversion and Expected Value in MDPs. - Marc Rigter; Paul Duckworth; Bruno Lacerda; Nick Hawes (ICAPS, 2022)

Shared Autonomy Systems with Stochastic Operator Models. - Clarissa Costen; Marc Rigter; Bruno Lacerda; Nick Hawes (IJCAI, 2022)

RAMBO-RL: Robust Adversarial Model-Based Offline Reinforcement Learning. - Marc Rigter; Bruno Lacerda; Nick Hawes (NeurIPS, 2022)

Planning with Hidden Parameter Polynomial MDPs. - Clarissa Costen; Marc Rigter; Bruno Lacerda; Nick Hawes (AAAI, 2023)

Risk-Constrained Planning for Multi-Agent Systems with Shared Resources. - Anna Gautier; Marc Rigter; Bruno Lacerda; Nick Hawes; Michael J. Wooldridge (AAMAS, 2023)

One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning. - Marc Rigter; Bruno Lacerda; Nick Hawes (NeurIPS, 2023)

Risk-Sensitive and Robust Model-Based Reinforcement Learning and Planning. - Marc Rigter (CoRR, 2023)

Reward-Free Curricula for Training Robust World Models. - Marc Rigter; Minqi Jiang; Ingmar Posner (ICLR, 2024)

TWIST: Teacher-Student World Model Distillation for Efficient Sim-to-Real Transfer. - Jun Yamada; Marc Rigter; Jack Collins; Ingmar Posner (ICRA, 2024)

AVID: Adapting Video Diffusion Models to World Models. - Marc Rigter; Tarun Gupta 002; Agrin Hilmkil; Chao Ma 019 (CoRR, 2024)

World Models via Policy-Guided Trajectory Diffusion. - Marc Rigter; Jun Yamada; Ingmar Posner (Trans. Mach. Learn. Res., 2024)