11 accepted papers
Efficiently learning interpretable policies for complex tasks from demonstrations is a challenging problem. We present Hierarchical Inference with Logical Options (HILO), a novel learning algorithm that learns to imitate expert demonstrations by learning the rules that the expert is following. The r
Symbolic reasoning is a key component for enabling practical use of data-driven planners in autonomous driving. In that context, deterministic finite state automata (DFA) are often used to formalize the underlying high-level decision-making process. Manual design of an effective DFA can be tedious.
Learning composable policies for environments with complex rules and tasks is a challenging problem. We introduce a hierarchical reinforcement learning framework called the Logical Options Framework (LOF) that learns policies that are satisfying, optimal, and composable. LOF efficiently learns polic…
This paper introduces the Logic-based Value Iteration Network (LVIN) framework, which combines imitation learning and logical automata to enable agents to learn complex behaviors from demonstrations. We address two problems with learning from expert knowledge: (1) how to generalize learned policies…
Among traffic accidents in the USA, 23% of fatal and 32% of non-fatal incidents occurred at intersections. For driver assistance systems, intersection navigation remains a difficult problem that is critically important to increasing driver safety. In this letter, we examine how to navigate an unsign
This paper introduces a new method for end-to-end training of deep neural networks (DNNs) and evaluates it in the context of autonomous driving. DNN training has been shown to result in high accuracy for perception to action learning given sufficient training data. However, the trained models may fa…
This work introduces a wearable system to provide situational awareness for blind and visually impaired people. The system includes a camera, an embedded computer and a haptic device to provide feedback when an obstacle is detected. The system uses techniques from computer vision and motion planning…
We present parametric trajectory optimization, a method for simultaneously computing physical parameters, actuation requirements, and robot motions for more efficient robot designs. In this scheme, robot dimensions, masses, and other physical parameters are solved for concurrently with traditional m…
The multi-robot path planning problem has been extensively studied for the cases of flying and driving vehicles. However, path planning for the case of vehicles that can both fly and drive has not yet been considered. Driving robots, while stable and energy efficient, are limited to mostly flat terr…
The agility and ease of control make a quadrotor aircraft an attractive platform for studying swarm behavior, modeling, and control. The energetics of sustained flight for small aircraft, however, limit typical applications to only a few minutes. Adding payloads - and the mechanisms used to manipula
While techniques exist for the rapid prototyping of mechanical and electrical components separately, this paper describes a method where commercial Additive Manufacturing (AM) techniques can be used to concurrently construct the mechanical structure and electronic circuits in a robotic or mechatroni…