Minimum Jerk Trajectory Planning for Trajectory Constrained Redundant Robots

In this dissertation, we develop an efficient method of generating minimal jerk trajectories for redundant robots in trajectory following problems. We show that high jerk is a local phenomenon, and therefore focus on optimizing regions of high jerk that occur when using traditional trajectory generation methods. The optimal trajectory is shown to be located on the foliation of self-motion manifolds, and this property is exploited to express the problem as a minimal dimension Bolza optimal control problem. A numerical algorithm based on ideas from pseudo-spectral optimization methods is proposed and applied to two example planar robot structures with two redundant degrees of freedom. When compared with existing trajectory generation methods, the proposed algorithm reduces the integral jerk of the examples by 75% and 13%. Peak jerk is reduced by 98% and 33%. Finally a real time controller is proposed to accurately track the planned trajectory given real-time measurements of the tool-tip\u27s following error

ENERGY MODELLING AND SIMULATION FOR INDUSTRIAL ROBOTS

openThis thesis explores energy modelling and simulation techniques tailored for industrial robots, with a primary objective of advancing energy efficiency. Focusing on the ABB-IRB-140 robot, the study utilizes MATLAB to develop comprehensive energy models for three distinct motions. The research unfolds through various objectives, including formulating kinematics, developing motion planning algorithms, conducting simulations, and constructing energy consumption models for individual robot joints. A pivotal aspect of this research lies in the development of a robust motion planning algorithm, recognized as a fundamental pillar that underpins the entire endeavour. This algorithm serves as a critical mechanism for optimizing energy efficiency and seamlessly integrating energy modelling techniques into real-world industrial applications. While MATLAB customization caters to specific robot characteristics, the developed algorithm boasts versatility, enabling its adaptation across a spectrum of industrial contexts and robot configurations. By elucidating the intricate relationship between motion planning and energy consumption in industrial robots, this research contributes to a deeper understanding of energy dynamics within the industrial landscape. Moreover, the insights gleaned hold the promise of significant advancements in energy-efficient robotics, fostering sustainable practices and mitigating the environmental impact associated with industrial operations. Ultimately, this thesis represents a crucial step forward in the quest for energy optimization, highlighting the transformative potential of interdisciplinary research at the nexus of engineering and sustainability

PACS Evolutionary Probe (PEP) - A Herschel Key Program

Deep far-infrared photometric surveys studying galaxy evolution and the nature of the cosmic infrared background are a key strength of the Herschel mission. We describe the scientific motivation for the PACS Evolutionary Probe (PEP) guaranteed time key program and its role in the complement of Herschel surveys, and the field selection which includes popular multiwavelength fields such as GOODS, COSMOS, Lockman Hole, ECDFS, EGS. We provide an account of the observing strategies and data reduction methods used. An overview of first science results illustrates the potential of PEP in providing calorimetric star formation rates for high redshift galaxy populations, thus testing and superseeding previous extrapolations from other wavelengths, and enabling a wide range of galaxy evolution studies.Comment: 13 pages, 12 figures, accepted for publication in A&