Trajectory generation for the N-trailer problem using Goursat normal form

Develops the machinery of exterior differential forms, more particularly the Goursat normal form for a Pfaffian system, for solving nonholonomic motion planning problems, i.e., motion planning for systems with nonintegrable velocity constraints. The authors use this technique to solve the problem of steering a mobile robot with n trailers. The authors present an algorithm for finding a family of transformations which will convert the system of rolling constraints on the wheels of the robot with n trailers into the Goursat canonical form. Two of these transformations are studied in detail. The Goursat normal form for exterior differential systems is dual to the so-called chained-form for vector fields that has been studied previously. Consequently, the authors are able to give the state feedback law and change of coordinates to convert the N-trailer system into chained-form. Three methods for planning trajectories for chained-form systems using sinusoids, piecewise constants, and polynomials as inputs are presented. The motion planning strategy is therefore to first convert the N-trailer system into Goursat form, use this to find the chained-form coordinates, plan a path for the corresponding chained-form system, and then transform the resulting trajectory back into the original coordinates. Simulations and frames of movie animations of the N-trailer system for parallel parking and backing into a loading dock using this strategy are included

Characterizing Energy Usage of a Commercially Available Ground Robot: Method and Results

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106934/1/rob21507.pd

Considerations for Task Allocation in Human-Robot Teams

In human-robot teams where agents collaborate together, there needs to be a clear allocation of tasks to agents. Task allocation can aid in achieving the presumed benefits of human-robot teams, such as improved team performance. Many task allocation methods have been proposed that include factors such as agent capability, availability, workload, fatigue, and task and domain-specific parameters. In this paper, selected work on task allocation is reviewed. In addition, some areas for continued and further consideration in task allocation are discussed. These areas include level of collaboration, novel tasks, unknown and dynamic agent capabilities, negotiation and fairness, and ethics. Where applicable, we also mention some of our work on task allocation. Through continued efforts and considerations in task allocation, human-robot teaming can be improved.Comment: Presented at AI-HRI symposium as part of AAAI-FSS 2022 (arXiv:2209.14292

Methods of measuring the size and complexity of PLC programs in different logic control design methodologies

Currently there is a wide variety of logic control design methodologies used in industrial logic design. These methodologies include ladder diagrams, function block diagrams, sequential function charts, and flow charts, but driven by a desire for verifiability, academics are developing additional logic control design methodologies, such as modular finite state machines and Petri nets. Using these, important properties of programs can be verified and some logic can be generated automatically from a part plan. The main contribution of this paper is to define methods for measuring programs written in different methodologies, so that the performance of the methodologies can be compared.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45886/1/170_2003_Article_1996.pd

Examining the effects of emotional valence and arousal on takeover performance in conditionally automated driving

In conditionally automated driving, drivers have difficulty in takeover transitions as they become increasingly decoupled from the operational level of driving. Factors influencing takeover performance, such as takeover lead time and the engagement of non-driving-related tasks, have been studied in the past. However, despite the important role emotions play in human-machine interaction and in manual driving, little is known about how emotions influence drivers’ takeover performance. This study, therefore, examined the effects of emotional valence and arousal on drivers’ takeover timeliness and quality in conditionally automated driving. We conducted a driving simulation experiment with 32 participants. Movie clips were played for emotion induction. Participants with different levels of emotional valence and arousal were required to take over control from automated driving, and their takeover time and quality were analyzed. Results indicate that positive valence led to better takeover quality in the form of a smaller maximum resulting acceleration and a smaller maximum resulting jerk. However, high arousal did not yield an advantage in takeover time. This study contributes to the literature by demonstrating how emotional valence and arousal affect takeover performance. The benefits of positive emotions carry over from manual driving to conditionally automated driving while the benefits of arousal do not

The New Mechanical Engineering Curriculum at the University of Michigan

This paper describes the new undergraduate program in the Department of Mechanical Engineering and Applied Mechanics at the University of Michigan, Ann Arbor. The restructuring of the program was initiated by a comprehensive review in 1992 that included surveys of alumni, students, and industrial representatives, as well as faculty assessment of current trends and future needs. The program is intended to address the changing backgrounds of incoming students, to prepare the students for new and diverse challenges in the workplace, and to provide a structure for the curriculum to evolve with changing technology. The new curriculum consists of three integrated courses in Design and Manufacturing, two Laboratory courses, and several redesigned courses in the Engineering Sciences. The redesigned program provides students with extensive hands‐on experience, a comprehensive experience in teamwork and technical communication, and the opportunity to exercise and develop their creativity.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94791/1/j.2168-9830.2001.tb00624.x.pd

Advanced nonlinear control : final project projects, Fall 1995

http://deepblue.lib.umich.edu/bitstream/2027.42/7961/5/bad2388.0001.001.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/7961/4/bad2388.0001.001.tx

Characterizing and Improving the Performance of Teleoperated Mobile Manipulators

Presented on September 11, 2013 from 12:00 pm - 1:00 pm in the TSRB Auditorium.Dawn M. Tilbury received a BS degree in electrical engineering, summa cum laude, from the University of Minnesota in 1989, and an MS and PhD degree in electrical engineering and computer sciences from the University of California, Berkeley, in 1992 and 1994, respectively. In 1995, she joined the faculty of the University of Michigan, Ann Arbor, where she is currently a professor of mechanical engineering with a joint appointment in Electrical Engineering and Computer Science. Tilbury’s research interests lie broadly in the area of control systems, including applications for robotics and manufacturing systems. She was program chair of ACC 2012 and will be general chair of ACC 2014. Tilbury is a life member of SWE, and Fellow of ASME and IEEE.Runtime: 51:57 minutes.Vehicles in racing simulation video games speed down virtual racecourses in excess of 100mph. However, teleoperated mobile manipulators in search and rescue operations inch along at an excruciatingly slow pace, even though time is of the essence. In both cases, the human operator is in the loop, giving control input to the vehicle. In the first case, however, the driver only needs to control the direction of the vehicle through a steering wheel or joystick; in the second case, the additional degrees of freedom of the manipulator arm are added. Of course, the environments are also different: a structured simulated world as opposed to a uncertain real disaster area. For multiple reasons including communications latency, actuator limitations, and inefficient human-robot interaction strategies, even basic robot teleoperation tasks are excruciatingly slow, both in robot mobility and manipulator arm control. For robots to become more useful tools for humans in the future, the speed at which robotassisted tasks can be completed must be increased. In this talk, I present a framework we have developed for characterizing and understanding the key factors that limit the performance of teleoperated mobile manipulators, where performance is defined as a combination of speed, accuracy and safety (lack of collisions). Our analysis framework depends on a having models of delay and performance for the different components of the system, and I describe some models that we have created based on user testing. We consider operator feedback using video and virtual reality, and compare a gamepad user input to a master-slave manipulator. Since adding semi-autonomous behaviors to a teleoperated robot can improve the performance, we describe our results in rollover prevention. I conclude with a discussion of future work in the area