Tag Archives: Useful For Teaching

On the increasing problem of writing quality of engineering students

September 25, 2023 11:20 ,

F. C. Berry, M. L. Phillips, J. Condron and P. A. Sanger, Improving Writing Quality of Capstone Reports, IEEE Transactions on Education, vol. 64, no. 4, pp. 383-389, Nov. 2021, DOI: 10.1109/TE.2021.3059739.

Contributions: The main contribution is to share a series of practical methods that improve the writing quality of capstone reports. Background: The ability to write well is critical to the success of an engineering technology graduate. However, the evidence points to the fact that industries are disappointed with the quality of writing skills graduates demonstrate. Intended Outcomes: A faculty review of capstone reports showed little improvement in writing quality from the first course to the second in a two-semester capstone sequence. Therefore, the instructors explored what actions were needed to improve the writing quality of the capstone reports. Application Design: Several changes in the capstone courses were developed and implemented. The changes included: 1) using instructional technology as a scaffolding to help frame the writing required for the course and 2) engaging students in iterative writing with feedback. Findings: The assessment data showed a significant improvement, at the 5% level. The iterative process of writing and rewriting the report, coupled with frequent meetings with faculty mentors, proved to be a powerful combination for improving the writing process of the students.

Posted in: Education , Tagged: ,

A so-called universal approach for modelling and controlling robots

June 28, 2023 10:25 ,

Tarokh, M., A unified kinematics modeling, optimization and control of universal robots: from serial and parallel manipulators to walking, rolling and hybrid robots, . Auton Robot 44, 1233–1248 (2020) DOI: 10.1007/s10514-020-09929-6.

The paper develops a unified kinematics modeling, optimization and control that is applicable to a wide range of autonomous and non-autonomous robots. These include hybrid robots that combine two or more modes of operations, such as combination of walking and rolling, or rolling and manipulation, as well as parallel robots in various configurations. The equations of motion are derived in compact forms that embed an optimization criterion. These equations are used to obtain various useful forms of the robot kinematics such as recursive, body and limb-end kinematic forms. Using the modeling, actuation and control equations are derived that ensure traversing a desired path while maintaining balanced operations and tip-over avoidance. Various simulation results are provided for a hybrid rolling-walking robot, which demonstrate the capabilities and effectiveness of the developed methodologies.

Posted in: Robot models , Tagged: , ,

Path planning by merging random sampling (RRT) with informed heuristics (A*)

September 14, 2021 12:44 ,

Jonathan D Gammell, Timothy D Barfoot, Siddhartha S Srinivasa, Batch Informed Trees (BIT*): Informed asymptotically optimal anytime search, The International Journal of Robotics Research. 2020;39(5):543-567, DOI: 10.1177/0278364919890396.

Path planning in robotics often requires finding high-quality solutions to continuously valued and/or high-dimensional problems. These problems are challenging and most planning algorithms instead solve simplified approximations. Popular approximations include graphs and random samples, as used by informed graph-based searches and anytime sampling-based planners, respectively.

Informed graph-based searches, such as A*, traditionally use heuristics to search a priori graphs in order of potential solution quality. This makes their search efficient, but leaves their performance dependent on the chosen approximation. If the resolution of the chosen approximation is too low, then they may not find a (suitable) solution, but if it is too high, then they may take a prohibitively long time to do so.

Anytime sampling-based planners, such as RRT*, traditionally use random sampling to approximate the problem domain incrementally. This allows them to increase resolution until a suitable solution is found, but makes their search dependent on the order of approximation. Arbitrary sequences of random samples approximate the problem domain in every direction simultaneously, but may be prohibitively inefficient at containing a solution.

This article unifies and extends these two approaches to develop Batch Informed Trees (BIT*), an informed, anytime sampling-based planner. BIT* solves continuous path planning problems efficiently by using sampling and heuristics to alternately approximate and search the problem domain. Its search is ordered by potential solution quality, as in A*, and its approximation improves indefinitely with additional computational time, as in RRT*. It is shown analytically to be almost-surely asymptotically optimal and experimentally to outperform existing sampling-based planners, especially on high-dimensional planning problems.

Posted in: Robot motion planning , Tagged: , , ,

On the formalization and conceptualization of real-time basic concepts and methods (RMS, EDF) for robots

October 10, 2019 14:39 ,

Nicolas Gobillot, Charles Lesire, David Doose, A Design and Analysis Methodology for Component-Based Real-Time Architectures of Autonomous Systems. Journal of Intelligent & Robotic Systems, October 2019, Volume 96, Issue 1, pp 123–138, DOI: 10.1007/s10846-018-0967-5.

The integration of autonomous robots in real applications is a challenge. It needs that the behaviour of these robots is proved to be safe. In this paper, we focus on the real-time software embedded on the robot, and that supports the execution of safe and autonomous behaviours. We propose a methodology that goes from the design of component-based software architectures using a Domain Specific Language, to the analysis of the real-time constraints that arise when considering the safety of software applications. This methodology is supported by a code generation toolchain that ensures that the code eventually executed on the robot is consistent with the analysis performed. This methodology is applied on a ground robot exploring an area.

Posted in: Real-Time Systems, Robotic software , Tagged: , , ,

A related work with a nice taxonomy of robot navigation algorithms

June 17, 2019 12:18 ,

Eduardo J. Molinos, Ángel Llamazares, Manuel Ocaña Dynamic window based approaches for avoiding obstacles in moving, Robotics and Autonomous Systems,
Volume 118, 2019, Pages 112-130 DOI: 10.1016/j.robot.2019.05.003.

In recent years, Unmanned Ground Vehicles (UGVs) have been widely used as service robots. Unlike industrial robots, which are situated in fixed and controlled positions, UGVs work in dynamic environments, sharing the environment with other vehicles and humans. These robots should be able to move without colliding with any obstacle, assuring its integrity and the environment safety. In this paper, we propose two adaptations of the classical Dynamic Window algorithm for dealing with dynamic obstacles like Dynamic Window for Dynamic Obstacles (DW4DO) and Dynamic Window for Dynamic Obstacles Tree (DW4DOT). These new algorithms are compared with our previous algorithms based on Curvature Velocity Methods: Predicted Curvature Velocity Method (PCVM) and Dynamic Curvature Velocity Method (DCVM). Proposals have been validated in both simulated and real environment using several robotic platforms.

Posted in: Robot motion planning , Tagged: ,

A nice introduction to psychological time

September 26, 2018 09:13 ,

Lindsey Drayton, Moran Furman, Thy Mind, Thy Brain and Time, Trends in Cognitive Sciences, olume 22, Issue 10, 2018, Pages 841-843 DOI: 10.1016/j.tics.2018.08.007.

The passage of time has fascinated the human mind for millennia. Tools for measuring time emerged early in civilization: lunar calendars appear in the archeological record as far back as 10 000 years ago and water clocks some 6000 years ago. Later technological innovations such as mechanical clocks, and more recently atomic clocks, have allowed the tracking of time with ever-increasing precision. And yet, arguably, the most sophisticated ‘time piece’ is the brain. Our brains can not only track the duration and succession of events, but they can also coordinate complex motor movements at striking levels of precision; communicate effectively by generating and interpreting sounds and speech; determine how to maximize rewards over time in the face of uncertainty; reflect upon the past; plan for the future; respond to temporal regularities and irregularities in the environment; and adapt to change in temporal scales that range from millisecond resolution up to evolutionary processes spanning millions of years.

Posted in: Cognitive sciences , Tagged: ,

A nice hybridization of RBPF, high-frequency scan matching and topological maps to perform SLAM, with an also nice state-of-the-art

September 19, 2018 08:52 ,

Aristeidis G. Thallas, Emmanouil G. Tsardoulias, Loukas Petrou, Topological Based Scan Matching – Odometry Posterior Sampling in RBPF Under Kinematic Model Failures, Journal of Intelligent & Robotic Systems, September 2018, Volume 91, Issue 3–4, pp 543–568, DOI: 10.1007/s10846-017-0730-3.

Rao-Blackwellized Particle Filters (RBPF) have been utilized to provide a solution to the SLAM problem. One of the main factors that cause RBPF failure is the potential particle impoverishment. Another popular approach to the SLAM problem are Scan Matching methods, whose good results require environments with lots of information, however fail in the lack thereof. To face these issues, in the current work techniques are presented to combine Rao-Blackwellized particle filters with a scan matching algorithm (CRSM SLAM). The particle filter maintains the correct hypothesis in environments lacking features and CRSM is employed in feature-rich environments while simultaneously reduces the particle filter dispersion. Since CRSM’s good performance is based on its high iteration frequency, a multi-threaded combination is presented which allows CRSM to operate while RBPF updates its particles. Additionally, a novel method utilizing topological information is proposed, in order to reduce the number of particle filter resamplings. Finally, we present methods to address anomalous situations where scan matching can not be performed and the vehicle displays behaviors not modeled by the kinematic model, causing the whole method to collapse. Numerous experiments are conducted to support the aforementioned methods’ advantages.

Posted in: Mobile robot SLAM , Tagged: , , , ,

A unifying framework for path planning in real-time (mainly for UAVs) and a nice summary of the state-of-the-art in modern path planning

September 19, 2018 08:42 ,

M. Murillo, G. SánchezL. GenzelisL. Giovanini, A Real-Time Path-Planning Algorithm based on Receding Horizon Techniques, Journal of Intelligent & Robotic Systems, September 2018, Volume 91, Issue 3–4, pp 445–457, DOI: 10.1007/s10846-017-0740-1.

In this article we present a real-time path-planning algorithm that can be used to generate optimal and feasible paths for any kind of unmanned vehicle (UV). The proposed algorithm is based on the use of a simplified particle vehicle (PV) model, which includes the basic dynamics and constraints of the UV, and an iterated non-linear model predictive control (NMPC) technique that computes the optimal velocity vector (magnitude and orientation angles) that allows the PV to move toward desired targets. The computed paths are guaranteed to be feasible for any UV because: i) the PV is configured with similar characteristics (dynamics and physical constraints) as the UV, and ii) the feasibility of the optimization problem is guaranteed by the use of the iterated NMPC algorithm. As demonstration of the capabilities of the proposed path-planning algorithm, we explore several simulation examples in different scenarios. We consider the existence of static and dynamic obstacles and a follower condition.

Posted in: Robot motion planning , Tagged: ,

On the use of flipped classroom for control engineering classes and its problem with the required (longer) time for learning

May 10, 2018 08:21 ,

Y. Kim and C. Ahn, Effect of Combined Use of Flipped Learning and Inquiry-Based Learning on a System Modeling and Control Course, IEEE Transactions on Education, vol. 61, no. 2, pp. 136-142, DOI: 10.1109/TE.2017.2774194.

Contribution: This paper illustrates how to design and implement curricula in terms of the combined use of flipped learning and inquiry-based learning in an engineering course. Background: Elementary courses in engineering schools are conventional and foundational, and involve a considerable amount of knowledge. Throughout such courses, students are also expected to develop insight, which cannot be obtained by only listening to instructors. Having relevant discussions is also difficult for most instructors. Intended Outcomes: The combined use of flipped learning and inquiry-based learning would be beneficial to broaden student achievement. Application Design: Based on an epistemological approach about knowledge and knowing, this paper applies the combined use of flipped learning and inquiry-based learning to enhance student knowledge and advance ways of thinking on a System Modeling and Control course. Findings: The extended learning time and the collective responsibility for learning are discussed as critical issues in applying the combined use of flipped learning and inquiry-based learning in an engineering school.

Posted in: Control Engineering, Education , Tagged: ,

A microprocessor designed for real-time predictability and short WCETs

March 26, 2018 08:58 ,

Schoeberl, M., Puffitsch, W., Hepp, S. et al, Patmos: a time-predictable microprocessor, Real-Time Syst (2018) 54: 389, DOI: 10.1007/s11241-018-9300-4.

Current processors provide high average-case performance, as they are optimized for general purpose computing. However, those optimizations often lead to a high worst-case execution time (WCET). WCET analysis tools model the architectural features that increase average-case performance. To keep analysis complexity manageable, those models need to abstract from implementation details. This abstraction further increases the WCET bound. This paper presents a way out of this dilemma: a processor designed for real-time systems. We design and optimize a processor, called Patmos, for low WCET bounds rather than for high average-case performance. Patmos is a dual-issue, statically scheduled RISC processor. A method cache serves as the cache for the instructions and a split cache organization simplifies the WCET analysis of the data cache. To fill the dual-issue pipeline with enough useful instructions, Patmos relies on a customized compiler. The compiler also plays a central role in optimizing the application for the WCET instead of average-case performance.

Posted in: Electronics, Real-Time Systems , Tagged: , ,