From the 1 of 6 linked papers with an AI index.
6 papers
Beyond Visual Grasping: Benchmarking Complex Grasping from Detection to Execution
Hanyi Zhang, Khang Nguyen, Charith Munasinghe +10
The paper introduces GCA-Bench, a new benchmark for evaluating robotic grasping in complex, multi-step scenarios that require scene-level reasoning and semantic constraints, and as…
Safe Flow Q-Learning: Offline Safe Reinforcement Learning with Reachability-Based Flow Policies
Mumuksh Tayal, Manan Tayal, Ravi Prakash
Offline safe reinforcement learning (RL) seeks reward-maximizing policies from static datasets under strict safety constraints. Existing methods often rely on soft expected-cost ob…
AffordMatcher: Affordance Learning in 3D Scenes from Visual Signifiers
Nghia Vu, Tuong Do, Khang Nguyen +8
Affordance learning is a complex challenge in many applications, where existing approaches primarily focus on the geometric structures, visual knowledge, and affordance labels of o…
Sequentially Teaching Sequential Tasks : Teaching Robots Long-horizon Manipulation Skills
Zlatan AjanoviÄ, Ravi Prakash, Leandro de Souza Rosa +1
Learning from demonstration has proved itself useful for teaching robots complex skills with high sample efficiency. However, teaching long-horizon tasks with multiple skills is ch…
Impedance Primitive-augmented Hierarchical Reinforcement Learning for Sequential Tasks
Amin Berjaoui Tahmaz, Ravi Prakash, Jens Kober
This paper presents an Impedance Primitive-augmented hierarchical reinforcement learning framework for efficient robotic manipulation in sequential contact tasks. We leverage this…
Generalizable Motion Policies through Keypoint Parameterization and Transportation Maps
Giovanni Franzese, Ravi Prakash, Cosimo Della Santina +1
Learning from Interactive Demonstrations has revolutionized the way non-expert humans teach robots. It is enough to kinesthetically move the robot around to teach pick-and-place, d…