4 papers
TGrasp6D: Task-Informed Vision-Language Priors and Pose Refinement enable Zero-Shot Task-Oriented 6DoF Grasping
Manav Kulshrestha, Apoorva Vashisth, Damon Conover +1
Task-Oriented Grasping (TOG) has emerged as an important skill for purposeful robotic manipulation. Given the task of using a knife to "slice bread," a robot must choose to grasp f…
CoReLIN: Constraint-based Reasoning for Zero-shot Lifelong Interactive Navigation
Apoorva Vashisth, Manav Kulshrestha, Pranav Bakshi +3
Robot navigation typically assumes an obstacle-free path exists between start and goal. In real environments, however, clutter may block all routes. We introduce Lifelong Interacti…
Scalable Multi-Robot Informative Path Planning for Target Mapping via Deep Reinforcement Learning
Apoorva Vashisth, Manav Kulshrestha, Damon Conover +1
Autonomous robots are widely utilized for mapping and exploration tasks due to their cost-effectiveness. Multi-robot systems offer scalability and efficiency, especially in terms o…
Deep Reinforcement Learning with Dynamic Graphs for Adaptive Informative Path Planning
Apoorva Vashisth, Julius Rückin, Federico Magistri +2
Autonomous robots are often employed for data collection due to their efficiency and low labour costs. A key task in robotic data acquisition is planning paths through an initially…