Robotic Manipulation and Control for Mobile Autonomous Platforms: Design and Implementation

  • Mohammad Shaqura

Student thesis: Doctoral Thesis


This thesis presents contributions to applied robotic control and manipulation in the areas of motion algorithm design, hardware, and software robotic system design. Mobile robotic systems are widely used in several applications. Control of such systems poses many challenges caused by system modeling uncertainty. Complex physics phenomena and environmental effects are usually neglected to simplify analysis and control design. In motion planning, this thesis introduces an algorithm for navigation learning in mobile robots that aims to reduce the effect of modeling uncertainties on control performance. Starting from an initial feasible state and input trajectories, the objective is to reduce navigation time through iterative trials. A nominal model of the actual system and the experimental system output are used to update the control input in every iteration for incremental improvement. The navigation problem is formulated as an optimal control problem that is solved after each trial to generate a vector of input deviations for the next trial. The formulation of the approach, simulation, and experimental results shows the effectiveness of the presented method. The design part focuses on developing hardware and software systems for manipulation and aerial robots. A software tool for automated generation of multirotor simulation models is developed utilizing CAD software API and Matlab. In the area of human-robot interaction, a human-supervised UAV inspection system has been developed and tested. The UAV is guided by a human operator using a handheld laser pointing device that is designed and fabricated in-house. In the field of robotic manipulation, a novel gripper mechanism is designed and implemented. The proposed mechanism targets applications where a grasped object lies in areas with limited surrounding clearance and where external torques affect the grasped object. This design was implemented on a mobile manipulation platform and tested during an international robotics competition.
Date of AwardAug 2018
Original languageEnglish (US)
Awarding Institution
  • Physical Sciences and Engineering
SupervisorJeff Shamma (Supervisor)


  • control
  • Robotics
  • Navigation
  • Manipulation
  • Grasp
  • Guidance

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