60 citations · 117 across the 10 of their papers we have counts for
10 papers
IR-SIM: A Lightweight Declarative Simulator for Navigation Learning and Benchmarking
Ruihua Han, Shuai Wang, Chengyang Li +8
Developing navigation policies requires simulation scenarios that support repeatable training and evaluation. Despite the availability of numerous simulators, constructing diverse…
RDA: An Accelerated Collision Free Motion Planner for Autonomous Navigation in Cluttered Environments
Ruihua Han, Shuai Wang, Shuaijun Wang +5
Autonomous motion planning is challenging in multi-obstacle environments due to nonconvex collision avoidance constraints. Directly applying numerical solvers to these nonconvex fo…
Federated Deep Learning Meets Autonomous Vehicle Perception: Design and Verification
Shuai Wang, Chengyang Li, Derrick Wing Kwan Ng +4
Realizing human-like perception is a challenge in open driving scenarios due to corner cases and visual occlusions. To gather knowledge of rare and occluded instances, federated le…
Robotic Wireless Energy Transfer in Dynamic Environments: System Design and Experimental Validation
Shuai Wang, Ruihua Han, Yuncong Hong +5
Wireless energy transfer (WET) is a ground-breaking technology for cutting the last wire between mobile sensors and power grids in smart cities. Yet, WET only offers effective tran…
Unit-Modulus Wireless Federated Learning Via Penalty Alternating Minimization
Shuai Wang, Dachuan Li, Rui Wang +3
Wireless federated learning (FL) is an emerging machine learning paradigm that trains a global parametric model from distributed datasets via wireless communications. This paper pr…
Distributed Dynamic Map Fusion via Federated Learning for Intelligent Networked Vehicles
Zijian Zhang, Shuai Wang, Yuncong Hong +2
The technology of dynamic map fusion among networked vehicles has been developed to enlarge sensing ranges and improve sensing accuracies for individual vehicles. This paper propos…
Edge Federated Learning Via Unit-Modulus Over-The-Air Computation
Shuai Wang, Yuncong Hong, Rui Wang +3
Edge federated learning (FL) is an emerging paradigm that trains a global parametric model from distributed datasets based on wireless communications. This paper proposes a unit-mo…
Learning Centric Wireless Resource Allocation for Edge Computing: Algorithm and Experiment
Liangkai Zhou, Yuncong Hong, Shuai Wang +4
Edge intelligence is an emerging network architecture that integrates sensing, communication, computing components, and supports various machine learning applications, where a fund…
Learning Centric Power Allocation for Edge Intelligence
Shuai Wang, Rui Wang, Qi Hao +2
While machine-type communication (MTC) devices generate massive data, they often cannot process this data due to limited energy and computation power. To this end, edge intelligenc…
Angle Aware User Cooperation for Secure Massive MIMO in Rician Fading Channel
Shuai Wang, Miaowen Wen, Minghua Xia +3
Massive multiple-input multiple-output communications can achieve high-level security by concentrating radio frequency signals towards the legitimate users. However, this system is…