A touching movement : force control turns machining robots into universal tools

ABB has written a new chapter in the book of robot applications. While in the past it had been a tedious and time-consuming effort to program a robot for delicate fine-tuning operations, robots can now learn how to best manage such tasks themselves. This innovative approach can reduce overall programming times by up to 80 percent for robots used to grind castings, vastly improving productivity levels. With ABB’s new Flex Finishing system featuring RobotWare Machining FC (force control), one of the last real barriers to productivity improvement in this sector has been lifted.

Placing sensors for area coverage in a complex environment by a team of robots

Existing solutions to carrier-based sensor placement by a single robot in a bounded unknown Region of Interest (ROI) do not guarantee full area coverage or termination. We propose a novel localized algorithm, named Back-Tracking Deployment (BTD). To construct a full coverage solution over the ROI, mobile robots (carriers) carry static sensors as payloads and drop them at the visited empty vertices of a virtual square, triangular, or hexagonal grid. A single robot will move in a predefined order of directional preference until a dead end is reached. Then it back-tracks to the nearest sensor adjacent to an empty vertex (an "entrance" to an unexplored/uncovered area) and resumes regular forward movement and sensor dropping from there. To save movement steps, the back-tracking is carried out along a locally identified shortcut. We extend the algorithm to support multiple robots that move independently and asynchronously. Once a robot reaches a dead end, it will back-track, giving preference to its own path. Otherwise, it will take over the back-track path of another robot by consulting with neighboring sensors. We prove that BTD terminates within finite time and produces full coverage when no (sensor or robot) failures occur. We also describe an approach to tolerate failures and an approach to balance workload among robots. We then evaluate BTD in comparison with the only competing algorithms SLD [Chang et al. 2009a] and LRV [Batalin and Sukhatme 2004] through simulation. In a specific failure-free scenario, SLD covers only 40-50% of the ROI, whereas BTD covers it in full. BTD involves significantly (80%) less robot moves and messages than LRV.

Impact of Assurance of Learning (AOL) in programming course for novices

One of the aims of any higher education institution is to align its curriculum with program learning goals. Programs which ensure proper learning have positive effects on students, instructors, departments and also on the higher education institution itself. This paper discusses the implementation and effects of Assurance Of Learning (AOL) processes on introductory programming (IP) courses. It elaborates five stages of AOL to align program learning goals with IP curriculum. Then, it discusses how the AOL process identifies shortcomings in the assessment methods of IP courses. Furthermore, it enlightens how the assessment findings, as a result of the AOL process, provide mechanisms to address the drawbacks during the delivery of such courses. Feedback on

Investigating the effects of personality traits on pair programming in a higher education setting through a family of experiments

Evidence from our systematic literature review revealed numerous inconsistencies in findings from the Pair Programming (PP) literature regarding the effects of personality on PP's effectiveness as a pedagogical tool. In particular: i) the effect of differing personality traits of pairs on the successful implementation of pair-programming (PP) within a higher education setting is still unclear, and ii) the personality instrument most often used had been Myers-Briggs Type Indicator (MBTI), despite being an indicator criticized by personality psychologists as unreliable in measuring an individual's personality traits. These issues motivated the research described in this paper. We conducted a series of five formal experiments (one of which was a replicated experiment), between 2009 and 2010, at the University of Auckland, to investigate the effects of personality composition on PP's effectiveness. Each experiment looked at a particular personality trait of the Five-Factor personality framework. This framework comprises five broad traits (Openness to experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism), and our experiments focused on three of these - Conscientiousness, Neuroticism, and Openness. A total of 594 undergraduate students participated as subjects. Overall, our findings for all five experiments, including the replication, showed that Conscientiousness and Neuroticism did not present a statistically significant effect upon paired students' academic performance. However, Openness played a significant role in differentiating paired students' academic performance. Participants' survey results also indicated that PP not only caused an increase in satisfaction and confidence levels but also brought enjoyment to the tutorial classes and enhanced students' motivation.

A taxonomy and mapping of computer-based critiquing tools

Critics have emerged in recent times as a specific tool feature to support users in computer-mediated tasks. These computer-supported critics provide proactive guidelines or suggestions for improvement to designs, code, and other digital artifacts. The concept of a critic has been adopted in various domains, including medical, programming, software engineering, design sketching, and others. Critics have been shown to be an effective mechanism for providing feedback to users. We propose a new critic taxonomy based on extensive review of the critic literature. The groups and elements of our critic taxonomy are presented and explained collectively with examples, including the mapping of 13 existing critic tools, predominantly for software engineering and programming education tasks to the taxonomy. We believe this critic taxonomy will assist others in identifying, categorizing, developing, and deploying computer-supported critics in a range of domains.

Empirical studies of pair programming for CS/SE teaching in higher education: a systematic literature review

The objective of this paper is to present the current evidence relative to the effectiveness of pair programming (PP) as a pedagogical tool in higher education CS/SE courses. We performed a systematic literature review (SLR) of empirical studies that investigated factors affecting the effectiveness of PP for CS/SE students and studies that measured the effectiveness of PP for CS/SE students. Seventy-four papers were used in our synthesis of evidence, and 14 compatibility factors that can potentially affect PP's effectiveness as a pedagogical tool were identified. Results showed that students' skill level was the factor that affected PP's effectiveness the most. The most common measure used to gauge PP's effectiveness was time spent on programming. In addition, students' satisfaction when using PP was overall higher than when working solo. Our meta-analyses showed that PP was effective in improving students' grades on assignments. Finally, in the studies that used quality as a measure of effectiveness, the number of test cases succeeded, academic performance, and expert opinion were the quality measures mostly applied. The results of this SLR show two clear gaps in this research field: 1) a lack of studies focusing on pair compatibility factors aimed at making PP an effective pedagogical tool and 2) a lack of studies investigating PP for software design/modeling tasks in conjunction with programming tasks.

Robot coordination for energy-balanced matching and sequence dispatch of robots to events

Given a set of events and a set of robots, the dispatch problem is to allocate one robot for each event to visit it. In a single round, each robot may be allowed to visit only one event (matching dispatch), or several events in a sequence (sequence dispatch). In a distributed setting, each event is discovered by a sensor and reported to a robot. Here, we present novel algorithms aimed at overcoming the shortcomings of several existing solutions. We propose pairwise distance based matching algorithm (PDM) to eliminate long edges by pairwise exchanges between matching pairs. Our sequence dispatch algorithm (SQD) iteratively finds the closest event-robot pair, includes the event in dispatch schedule of the selected robot and updates its position accordingly. When event-robot distances are multiplied by robot resistance (inverse of the remaining energy), the corresponding energy-balanced variants are obtained. We also present generalizations which handle multiple visits and timing constraints. Our localized algorithm MAD is based on information mesh infrastructure and local auctions within the robot network for obtaining the optimal dispatch schedule for each robot. The simulations conducted confirm the advantages of our algorithms over other existing solutions in terms of average robot-event distance and lifetime.

A unified mixed-integer programming model for simultaneous fluence weight and aperture optimization in VMAT, tomotherapy, and cyberknife

All rights reserved. In this paper, we propose and study a unified mixed-integer programming model that simultaneously optimizes fluence weights and multi-leaf collimator (MLC) apertures in the treatment planning optimization of VMAT, Tomotherapy, and CyberKnife. The contribution of our model is threefold: (i) Our model optimizes the fluence and MLC apertures simultaneously for a given set of control points. (ii) Our model can incorporate all volume limits or dose upper bounds for organs at risk (OAR) and dose lower bound limits for planning target volumes (PTV) as hard constraints, but it can also relax either of these constraint sets in a Lagrangian fashion and keep the other set as hard constraints. (iii) For faster solutions, we propose several heuristic methods based on the MIP model, as well as a meta-heuristic approach. The meta-heuristic is very efficient in practice, being able to generate dose- and machinery-feasible solutions for problem instances of clinical scale, e.g., obtaining feasible treatment plans to cases with 180 control points, 6750 sample voxels and 18,000 beamlets in 470 seconds, or cases with 72 control points, 8000 sample voxels and 28,800 beamlets in 352 seconds. With discretization and down-sampling of voxels, our method is capable of tackling a treatment field of 8000-64,000cm3, depending on the ratio of critical structure versus unspecified tissues.

Spiking neural network-based target tracking control for autonomous mobile robots

In this paper, a target tracking controller based on spiking neural network is proposed for autonomous robots. This controller encodes the preprocessed environmental and target information provided by CCD cameras, encoders and ultrasonic sensors into spike trains, which are integrated by a three-layer spiking neural network (SNN). The outputs of SNN are generated based on the competition between the forward/backward neuron pair corresponding to each motor, with the weights evolved by the Hebbian learning. The application to target tracking of a mobile robot in unknown environment verifies the validity of the proposed controller.

A model for teaching an introductory programming course using ADRI

High failure and drop-out rates from introductory programming courses continue to be of significant concern to computer science disciplines despite extensive research attempting to address the issue. In this study, we include the three entities of the didactic triangle, instructors, students and curriculum, to explore the learning difficulties that students encounter when studying introductory programming. We first explore students’ perceptions of the barriers and affordances to learning programming. A survey is conducted with introductory programming students to get their feedback on the topics and associated learning resources in the introductory programming course. The instructors’ perceptions are included by analyzing current teaching materials and assessment tools used in the course. As a result, an ADRI based approach is proposed to address the problems identified in the teaching and learning processes of an introductory programming course.