Autonomous Robots Lab

Motion Planning

Wed, 06 Jul 2022 00:00:00 +0000

Applications of autonomous robots in dynamic, uncertain environments, such as crowded traffic, overwhelmed workspace, or unexplored wilderness, has posed significant challenges to the design of motion planning algorithms. We develop efficient trajectory optimization approaches for autonomous vehicles to drive in a smooth and safe manner in structured traffic environments, and for robot swarms to efficiently coordinate and safely navigate in unknown environments.

Active Sensing

Wed, 06 Jul 2022 00:00:00 +0000

Active sensing refers to using autonomous robots to proactively explore an unknown environment or gather information of object states, and it holds great potential for both civil and military applications, such as search and rescue, environmental monitoring, surveillance and reconnaissance. In the active sensing, both motion planning and perception are inherently coupled in that trajectories determine the informativeness of observations, and the observations in turn guide the trajectory generation. The abilitiy to generate informative paths/trajectories is the key factor in successful active sensing.

Among various tasks of active sensing, we focus on target search and tracking using autonomous robots. We develop informative-theoretic trajectory planning approaches for mobile robots to actively search and track moving targets, the motion models of which can be linear, nonlinear, or even unknown a priori.

Distributed Filtering

Wed, 06 Jul 2022 00:00:00 +0000

Distributed filtering using multiple mobile robots has many important applications such as environmental monitoring, SLAM, and target localization. While significant achievements have been made for distributed linear filtering, the counterparts for nonlinear filtering techniques fall short.

We propose a measurement dissemination-based distributed Bayesian filter for nonlinear estimation of target position under either fixed or time-variant communication topologies. Such method has been shown to generate consistent estimation and fast convergence performance.

Human Robot Collaboration

Wed, 06 Jul 2022 00:00:00 +0000

Intention-Aware Robots Human-robot Interaction (HRI) has been an increasingly popular research area due to the boom in personal and industrial robots. We are especially interested in enabling robots to collaborate as peers with the human. On one hand, we utilize Bayesian inference approach to help robots identify human’s intention and then provide assistance accordingly. On the other hand, we model how human anticipates the collaborative robot’s plan based on the partial actions that the robot has made. These two aspects close the interaction loop between human and robot and can be useful for developing algorithms to improve human-robot collaboration.

Companion Robot With robots stepping into daily life of human beings, various applications for improving human life qualify has been envisioned. We are interested in enabling robots to work as companions of humans, walking with a target human while carrying items for the human. Especially, we have developed a trajectory planning algorithm for robots to autonomously follow a target human, using onboard cameras.Due to the uncertainty in human’s motion, we proposed a Parallel Interacting Multiple Model-Unscented Kalman Filter (PIMM-UKF) approch for human motion estimation and prediction. Based on the predicted human states, an MPC path planner is developed to produce safe and comfortable following trajectory of the robot.

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Sat, 01 Jun 2030 13:00:00 +0000

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Online Action Change Detection for Automatic Vision-based Ground Control of Aircraft

Sun, 23 Jan 2022 22:54:47 +0800

Adaptive online distributed optimal control of very-large-scale robotic systems

Fri, 01 Jan 2021 00:00:00 +0000

Jian Yang and Monica Hall Win the Best Paper Award at Wowchemy 2020

Wed, 02 Dec 2020 00:00:00 +0000

Congratulations to Jian Yang and Monica Hall for winning the Best Paper Award at the 2020 Conference on Wowchemy for their paper “Learning Wowchemy”.

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Richard Hendricks Wins First Place in the Wowchemy Prize

Tue, 01 Dec 2020 00:00:00 +0000

Congratulations to Richard Hendricks for winning first place in the Wowchemy Prize.

Mixed reinforcement learning for efficient policy optimization in stochastic environments

Wed, 01 Jan 2020 00:00:00 +0000

Rumor-robust Decentralized Gaussian Process Learning, Fusion, and Planning for Modeling Multiple Moving Targets

Wed, 01 Jan 2020 00:00:00 +0000

Learning recursive bayesian nonparametric modeling of moving targets via mobile decentralized sensors

Tue, 01 Jan 2019 00:00:00 +0000

Vision-guided planning and control for autonomous taxiing via convolutional neural networks

Tue, 01 Jan 2019 00:00:00 +0000

Distributed Bayesian Filter Using Measurement Dissemination for Multiple Unmanned Ground Vehicles With Dynamically Changing Interaction Topologies

Mon, 01 Jan 2018 00:00:00 +0000

Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles

Mon, 01 Jan 2018 00:00:00 +0000

Scene understanding in deep learning-based end-to-end controllers for autonomous vehicles

Mon, 01 Jan 2018 00:00:00 +0000

Distributed Bayesian filters for multi-vehicle network by using Latest-In-and-Full-Out exchange protocol of measurements