11 papers
PointMapPolicy: Structured Point Cloud Processing for Multi-Modal Imitation Learning
Xiaogang Jia, Qian Wang, Anrui Wang +12
Robotic manipulation systems benefit from complementary sensing modalities, where each provides unique environmental information. Point clouds capture detailed geometric structure,…
MoRe-ERL: Learning Motion Residuals using Episodic Reinforcement Learning
Xi Huang, Hongyi Zhou, Ge Li +5
We propose MoRe-ERL, a framework that combines Episodic Reinforcement Learning (ERL) and residual learning, which refines preplanned reference trajectories into safe, feasible, and…
BEAST: Efficient Tokenization of B-Splines Encoded Action Sequences for Imitation Learning
Hongyi Zhou, Weiran Liao, Xi Huang +11
We present the B-spline Encoded Action Sequence Tokenizer (BEAST), a novel action tokenizer that encodes action sequences into compact discrete or continuous tokens using B-splines…
X-IL: Exploring the Design Space of Imitation Learning Policies
Xiaogang Jia, Atalay Donat, Xi Huang +8
Designing modern imitation learning (IL) policies requires making numerous decisions, including the selection of feature encoding, architecture, policy representation, and more. As…
Towards Fusing Point Cloud and Visual Representations for Imitation Learning
Atalay Donat, Xiaogang Jia, Xi Huang +7
Learning for manipulation requires using policies that have access to rich sensory information such as point clouds or RGB images. Point clouds efficiently capture geometric struct…
ETA-IK: Execution-Time-Aware Inverse Kinematics for Dual-Arm Systems
Yucheng Tang, Xi Huang, Yongzhou Zhang +3
This paper presents ETA-IK, a novel Execution-Time-Aware Inverse Kinematics method tailored for dual-arm robotic systems. The primary goal is to optimize motion execution time by l…
HIRO: Heuristics Informed Robot Online Path Planning Using Pre-computed Deterministic Roadmaps
Xi Huang, Gergely Sóti, Hongyi Zhou +3
With the goal of efficiently computing collision-free robot motion trajectories in dynamically changing environments, we present results of a novel method for Heuristics Informed R…
Planning with Learned Subgoals Selected by Temporal Information
Xi Huang, Gergely Sóti, Christoph Ledermann +2
Path planning in a changing environment is a challenging task in robotics, as moving objects impose time-dependent constraints. Recent planning methods primarily focus on the spati…
dGrasp: NeRF-Informed Implicit Grasp Policies with Supervised Optimization Slopes
Gergely Sóti, Xi Huang, Christian Wurll +1
We present dGrasp, an implicit grasp policy with an enhanced optimization landscape. This landscape is defined by a NeRF-informed grasp value function. The neural network represent…
6-DoF Grasp Pose Evaluation and Optimization via Transfer Learning from NeRFs
Gergely Sóti, Xi Huang, Christian Wurll +1
We address the problem of robotic grasping of known and unknown objects using implicit behavior cloning. We train a grasp evaluation model from a small number of demonstrations tha…
Train What You Know -- Precise Pick-and-Place with Transporter Networks
Gergely Sóti, Xi Huang, Christian Wurll +1
Precise pick-and-place is essential in robotic applications. To this end, we define a novel exact training method and an iterative inference method that improve pick-and-place prec…