7 accepted papers
Robotic manipulation requires explicit or implicit knowledge of the robot's joint positions. Precise proprioception is standard in high-quality industrial robots but is often unavailable in inexpensive robots operating in unstructured environments. In this paper, we ask: to what extent can a fast, s…
Gas distribution mapping (GDM) refers to the task of mapping the gas concentrations of an airborne chemical over a region of interest. A mobile robot equipped with a gas sensor can be used potentially autonomously to build such a distribution map. However, modern-day robots might not have enough bat
In a gas distribution mapping (GDM) task, the objective of a mobile robot is to map the gas concentrations of an airborne chemical over a region of interest using onboard sensing. Given the limited battery budget available to the robot, covering the entire area to measure gas concentrations at every…
Large Language Models (LLMs) are progressively being utilized as machine learning services and interface tools for various applications. However, the security implications of LLMs, particularly in relation to adversarial and Trojan attacks, remain insufficiently examined. In this paper, we propose T…
Multi-robot teams are becoming an increasingly popular approach for information gathering in large geographic areas, with applications in precision agriculture, surveying the aftermath of natural disasters or tracking pollution. These robot teams are often assembled from untrusted devices not owned…
Recent research demonstrated that it is feasible to end-to-end train multi-task deep visuomotor policies for robotic manipulation using variations of learning from demonstration (LfD) and reinforcement learning (RL). In this paper, we extend the capabilities of end-to-end LfD architectures to object…
We propose a technique for multi-task learning from demonstration that trains the controller of a low-cost robotic arm to accomplish several complex picking and placing tasks, as well as non-prehensile manipulation. The controller is a recurrent neural network using raw images as input and generatin…