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Arthur Richards

8 accepted papers

2023

Mode-constrained Model-based Reinforcement Learning via Gaussian Processes

AISTATS 2023poster

Model-based reinforcement learning (RL) algorithms do not typically consider environments with multiple dynamic modes, where it is beneficial to avoid inoperable or undesirable modes. We present a model-based RL algorithm that constrains training to a single dynamic mode with high probability. This…

2021

Fast Generation of Obstacle-Avoiding Motion Primitives for Quadrotors

IROS 2021poster

This work considers the problem of generating computationally efficient quadrotor motion primitives between a given pose (position, velocity, and acceleration) and a goal plane in the presence of obstacles. A new motion primitive tool based on the logistic curve is proposed and a closed-form analyti…

Cited by 1Source ↗Scholar ↗
2021

Reactive Visual Odometry Scheduling Based on Noise Analysis using an Adaptive Extended Kalman Filter

IROS 2021poster

A new strategy is proposed for scheduling Visual Odometry (VO) measurements for wheeled ground vehicles. Rather than having a fixed interval or distance between image acquisitions, we propose to trigger VO based on covariances from an Adaptive Extended Kalman Filter. The adopted model uses process n…

Cited by 1Source ↗Scholar ↗
2021

Trajectory Optimisation in Learned Multimodal Dynamical Systems via Latent-ODE Collocation

ICRA 2021poster

This paper presents a two-stage method to perform trajectory optimisation in multimodal dynamical systems with unknown nonlinear stochastic transition dynamics. The method finds trajectories that remain in a preferred dynamics mode where possible and in regions of the transition dynamics model that…

Cited by 12Source ↗Scholar ↗
2017

Robot navigation using convex model predictive control and approximate operating region optimization

IROS 2017poster

A method for real-time robot navigation with obstacle avoidance is presented. A two-stage approach is proposed: the use of online Simulated Annealing (SA) to optimize a convex operating region in configuration space is paired with Model Predictive Control (MPC) to determine a locally optimal motion…

Cited by 4Source ↗Scholar ↗