5 accepted papers
Payload-adaptive locomotion is an essential capability for quadruped robots operating in real-world scenarios, particularly when tasked with transporting dynamic payloads. Existing approaches face fundamental limitations: reactive adaptation strategies respond too slowly to sudden payload changes, w…
Adaptive locomotion is a fundamental capability for quadruped robots, particularly in real-world scenarios when they must transport novel or out-of-distribution (O.O.D.) payloads across diverse terrains. Previous learning-based methods often tightly couple a locomotion controller's learned parameter
Autonomous ground robots navigating unstructured off-road environments face perceptual challenges, such as sensor obscuration or failure, which can lead to inaccurate perception or navigation failures. While robot adaptation has recently gained increasing attention, self-reflective robot adaptation,
Sample-based motion planning approaches, such as RRT*, have been widely adopted in robotics due to their support for high-dimensional state spaces and guarantees of completeness and optimality. This paper introduces an RRT* approach (ORRT*) that leverages opportunism to (1) find solutions quickly, (…
This paper introduces a method, Generative Adversarial Networks for Detecting Erroneous Results (GANDER), leveraging Generative Adversarial Networks to provide online error detection in manipulation tasks for autonomous robot systems. GANDER relies on mapping input images of a trained task to a lear…