8 accepted papers
We introduce ET-Former, a novel end-to-end algorithm for semantic scene completion using a single monocular camera. Our approach generates a semantic occupancy map from single RGB observation while simultaneously providing uncertainty estimates for semantic predictions. By designing a triplane-based
When a mobile robot autonomously explores an indoor space to produce a localization and navigation map, it is important to create both a stable pose graph and a high-quality occupancy map that covers all the navigable areas. In this work, we propose a novel probabilistic active loop closure framewor…
In this paper, we present a probabilistic and unconstrained model predictive control formulation for robot navigation under uncertainty. We present (1) a closed-form approximation of the probability of collision that naturally models the propagation of uncertainty over the planning horizon and is co…
We present an algorithm for safe robot navigation in complex dynamic environments using a variant of model predictive equilibrium point control. We use an optimization formulation to navigate robots gracefully in dynamic environments by optimizing over a trajectory cost function at each timestep. We…
Autonomous exploration to build a map of an unknown environment is a fundamental robotics problem. However, the quality of the map directly influences the quality of subsequent robot operation. Instability in a simultaneous localization and mapping (SLAM) system can lead to poor-quality maps and sub…
Autonomous mobile robots need maps for effective, safe navigation, and SLAM in general is still an unsolved problem. Nonetheless, certain combinations of environmental characteristics and sensors admit tractable solutions. In particular, detection and tracking of linear features such as line segment…
Fast and high-fidelity dynamic model is very useful for planning, control, and estimation. Here, we present a fixed-time-step, discrete-time dynamic model of differential-drive vehicle with friction for reliable velocity prediction, which is fast, stable, and easy to calibrate. Unlike existing metho…
Here we present a non-holonomic distance function for unicycle-type vehicles, and use this distance function to extend the optimal path planner RRT* to handle nonholonomic constraints. The critical feature of our proposed distance function is that it is also a control-Lyapunov function. We show that…