4 accepted papers
Motion planning under uncertainty is one of the main challenges in developing autonomous driving vehicles. In this work, we focus on the uncertainty in sensing and perception, resulted from a limited field of view, occlusions, and sensing range. This problem is often tackled by considering hypotheti…
This paper presents a novel method to generate spatial constraints for motion planning in dynamic environments. Motion planning methods for autonomous driving and mobile robots typically need to rely on the spatial constraints imposed by a map-based global planner to generate a collision-free trajec…
Interaction is fundamental in autonomous driving (AD). Despite more than a decade of intensive R&D in AD, how to dynamically interact with diverse road users in various contexts still remains unsolved. Multi-agent learning has recently seen big breakthroughs and has much to offer towards solving rea
Tendon-driven mechanisms used in robotic surgery exhibit strong nonlinearities, particularly a static backlash-like hysteresis, in their motion transmission behavior. In this paper, an extension of a previously developed model is proposed that allows for estimation of angular displacements in multi-…