Aerial Physical Intelligence | ACP Lab

VBT-MPC: Vision-Based Tactile MPC for Contour Following

Wed, 13 May 2026 00:00:00 +0000

ES-HPC-MPC: Exponentially Stable Hybrid Perception Constrained MPC for Quadrotor with Suspended Payloads

Wed, 29 Oct 2025 00:00:00 +0000

PolyFly: Polytopic Optimal Planning for Collision-Free Cable-Suspended Aerial Payload Transportation

Fri, 17 Oct 2025 00:00:00 +0000

Human-Aware Physical Human-Robot Collaborative Transportation and Manipulation with Multiple Aerial Robots

Wed, 01 Jan 2025 00:00:00 +0000

Optimal Trajectory Planning for Cooperative Manipulation with Multiple Quadrotors Using Control Barrier Functions

Sun, 01 Sep 2024 00:00:00 +0000

HPA-MPC: Hybrid Perception-Aware Nonlinear Model Predictive Control for Quadrotors with Suspended Loads

Mon, 01 Jan 2024 00:00:00 +0000

RotorTM: A Flexible Simulator for Aerial Transportation and Manipulation

Mon, 01 Jan 2024 00:00:00 +0000

Nonlinear Model Predictive Control for Cooperative Transportation and Manipulation of Cable Suspended Payloads with Multiple Quadrotors

Sun, 01 Jan 2023 00:00:00 +0000

Aggressive Visual Perching with Quadrotors on Inclined Surfaces

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

Cooperative Transportation of Cable Suspended Payloads With MAVs Using Monocular Vision and Inertial Sensing

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

Design and Experimental Evaluation of Distributed Cooperative Transportation of Cable Suspended Payloads with Micro Aerial Vehicles

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

PCMPC: Perception-Constrained Model Predictive Control for Quadrotors with Suspended Loads using a Single Camera and IMU

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

Abstract:

In this paper, we address the Perception–Constrained Model Predictive Control (PCMPC) and state estimation problems for quadrotors with cable suspended payloads using a single camera and Inertial Measurement Unit (IMU). We design a receding–horizon control strategy for cable suspended payloads directly formulated on the system manifold configuration space SE(3)xS^2. The approach considers the system dynamics, actuator limits and the camera’s Field Of View (FOV) constraint to guarantee the payload’s visibility during motion. The monocular camera, IMU, and vehicle’s motor speeds are combined to provide estimation of the vehicle’s states in 3D space, the payload’s states, the cable’s direction and velocity. The proposed control and state estimation solution runs in real-time at 500 Hz on a small quadrotor equipped with a limited computational unit. The approach is validated through experimental results considering a cable suspended payload trajectory tracking problem at different speeds.