In this essay, I reflect on the way planning concepts, techniques, instruments and the general idea of 'planning' itself flow from one place to another, particularly in the context of the ...transnational flow of planning ideas. In the past, our conception of such flows was underpinned by linear and singular models of development pathways – the 'modernization' myth. This rendered them apparently benign and positive contributions to 'development'. Today, such concepts have been replaced by a recognition of contingency and complexity, which highlights the particular histories and challenges of localities in different parts of the world, and the damaging consequences when external ideas about planning and development are planted upon specific histories and geographies. This refocusing in turn raises questions about any general meaning of 'planning' as a universal good technology for complex urbanized societies. The paper reviews these shifts in conception, and then considers firstly how, as planning academics and practitioners, we should build narratives around particular 'travelling' planning ideas, to help critical learning in places where such ideas get to 'land'. Secondly, I suggest how the idea of 'planning' itself might be approached, as a general concept contingently evolving through the experiences and debates we engage in as a 'community of inquirers' through which we compose and construct our field of interest. In such a formulation, the general idea of planning is lodged in the tradition of experience, innovation, debate and critique which have accumulated around the practices of managing co-existence in complex urbanized societies.
In the 1960s, socialist and capitalist urban planners, architects, and city officials chose the urban periphery as the site to test out new ideas in modernist architecture and planning: the outskirts ...of Prague and a bedroom suburb of Toronto would be the sites for experimental urban development. In the Suburbs of History overcomes the divisions between East and West to reassemble the shared histories of modern architecture and urbanism as it shaped and re-shaped the periphery. Drawing on archives, interviews, architectural journals, and site visits to the peripheries of Prague and Toronto, Steven Logan reveals the intertwined histories of capitalist and socialist urban planning. From socialist utopias to the capitalist visions of the edge city, the history of the suburbs is not simply a history of competing urban forms; rather, it is a history of alternatives that advocated collective solutions over the dominant model of single-family home ownership and car-dominated spaces.
In this article, we present a framework for visual action planning of complex manipulation tasks with high-dimensional state spaces, focusing on manipulation of deformable objects. We propose a ...latent space roadmap (LSR) for task planning, which is a graph-based structure globally capturing the system dynamics in a low-dimensional latent space. Our framework consists of the following three parts. First, a mapping module (MM) that maps observations is given in the form of images into a structured latent space extracting the respective states as well as generates observations from the latent states. Second, the LSR, which builds and connects clusters containing similar states in order to find the latent plans between start and goal states, extracted by MM. Third, the action proposal module that complements the latent plan found by the LSR with the corresponding actions. We present a thorough investigation of our framework on simulated box stacking and rope/box manipulation tasks, and a folding task executed on a real robot.
Intelligent vehicles have increased their capabilities for highly and, even fully, automated driving under controlled environments. Scene information is received using onboard sensors and ...communication network systems, i.e., infrastructure and other vehicles. Considering the available information, different motion planning and control techniques have been implemented to autonomously driving on complex environments. The main goal is focused on executing strategies to improve safety, comfort, and energy optimization. However, research challenges such as navigation in urban dynamic environments with obstacle avoidance capabilities, i.e., vulnerable road users (VRU) and vehicles, and cooperative maneuvers among automated and semi-automated vehicles still need further efforts for a real environment implementation. This paper presents a review of motion planning techniques implemented in the intelligent vehicles literature. A description of the technique used by research teams, their contributions in motion planning, and a comparison among these techniques is also presented. Relevant works in the overtaking and obstacle avoidance maneuvers are presented, allowing the understanding of the gaps and challenges to be addressed in the next years. Finally, an overview of future research direction and applications is given.
Many exciting robotic applications require multiple robots with many degrees of freedom, such as manipulators, to coordinate their motion in a shared workspace. Discovering high-quality paths in such ...scenarios can be achieved, in principle, by exploring the composite space of all robots. Sampling-based planners do so by building a roadmap or a tree data structure in the corresponding configuration space and can achieve asymptotic optimality. The hardness of motion planning, however, renders the explicit construction of such structures in the composite space of multiple robots impractical. This work proposes a scalable solution for such coupled multi-robot problems, which provides desirable path-quality guarantees and is also computationally efficient. In particular, the proposed
dRRT
∗
is an informed, asymptotically-optimal extension of a prior sampling-based multi-robot motion planner,
dRRT
. The prior approach introduced the idea of building roadmaps for each robot and implicitly searching the tensor product of these structures in the composite space. This work identifies the conditions for convergence to optimal paths in multi-robot problems, which the prior method was not achieving. Building on this analysis,
dRRT
is first properly adapted so as to achieve the theoretical guarantees and then further extended so as to make use of effective heuristics when searching the composite space of all robots. The case where the various robots share some degrees of freedom is also studied. Evaluation in simulation indicates that the new algorithm,
dRRT
∗
converges to high-quality paths quickly and scales to a higher number of robots where various alternatives fail. This work also demonstrates the planner’s capability to solve problems involving multiple real-world robotic arms.
EB-RRT: Optimal Motion Planning for Mobile Robots Wang, Jiankun; Meng, Max Q.-H.; Khatib, Oussama
IEEE transactions on automation science and engineering,
10/2020, Volume:
17, Issue:
4
Journal Article
In a human-robot coexisting environment, it is pivotal for a mobile service robot to arrive at the goal position safely and efficiently. In this article, an elastic band-based rapidly exploring ...random tree (EB-RRT) algorithm is proposed to achieve real-time optimal motion planning for the mobile robot in the dynamic environment, which can maintain a homotopy optimal trajectory based on current heuristic trajectory. Inspired by the EB method, we propose a hierarchical framework consisting of two planners. In the global planner, a time-based RRT algorithm is used to generate a feasible heuristic trajectory for a specific task in the dynamic environment. However, this heuristic trajectory is nonoptimal. In the dynamic replanner, the time-based nodes on the heuristic trajectory are updated due to the internal contraction force and the repulsive force from the obstacles. In this way, the heuristic trajectory is optimized continuously, and the final trajectory can be proved to be optimal in the homotopy class of the heuristic trajectory. Simulation experiments reveal that compared with two state-of-the-art algorithms, our proposed method can achieve better performance in dynamic environments. Note to Practitioners -The motivation of this work stems from the need to achieve real-time optimal motion planning for the mobile robot in the human-robot coexisting environment. Sampling-based algorithms are widely used in this area due to their good scalability and high efficiency. However, the generated trajectory is usually far from optimal. To obtain an optimized trajectory for the mobile robot in the dynamic environment with moving pedestrians, we propose the EB-RRT algorithm on the basis of the time-based RRT tree and the EB method. Depending on the time-based RRT tree, we quickly get a heuristic trajectory and guarantee the probabilistic completeness of our algorithm. Then, we optimize the heuristic trajectory similar to the EB method, which achieves the homotopy optimality of the final trajectory. We also take into account the nonholonomic constraints, and our proposed algorithm can be applied to most mobile robots to further improve their motion planning ability and the trajectory quality.
A local plan is a statutory policy document that supports urban development decisions across a local government area in England. Local plans are reported to need more specific requirements for ...development proposals regarding wider health determinants to address potential health outcomes and health inequalities. This study reviews the integration of Health in Local Plans of seven local planning authorities through documentary analysis methods. A review framework was formulated based on health and planning literature regarding local plans, health policy and determinants of health and dialogue with a local government partner. The findings identify opportunities to strengthen the consideration of Health in Local Plans, including ensuring that policies are informed by local health priorities and signpost national guidance, strengthening health-related requirements for developers (e.g., indoor air quality, fuel poverty and security of tenure) and improving implementation of requirements for developers (e.g., through adoption of health management plans and community ownership). The study identifies further research needs regarding how policies are interpreted by developers in practice, and on national guidance for Health Impact Assessment. It highlights the benefit of undertaking a comparative review, contrasting local plan policy language and identifying opportunities to share, adapt and strengthen planning requirements regarding health outcomes.
Optimization-Based Collision Avoidance Zhang, Xiaojing; Liniger, Alexander; Borrelli, Francesco
IEEE transactions on control systems technology
29, Issue:
3
Journal Article
Peer reviewed
Open access
This article presents a novel method for exactly reformulating nondifferentiable collision avoidance constraints into smooth, differentiable constraints using strong duality of convex optimization. ...We focus on a controlled object whose goal is to avoid obstacles while moving in an <inline-formula> <tex-math notation="LaTeX">n </tex-math></inline-formula>-dimensional space. The proposed reformulation is exact, does not introduce any approximations, and applies to general obstacles and controlled objects that can be represented as the union of convex sets. We connect our results with the notion of signed distance, which is widely used in traditional trajectory generation algorithms. Our method can be applied to generic navigation and trajectory planning tasks, and the smoothness property allows the use of general-purpose gradient- and Hessian-based optimization algorithms. Finally, in case a collision cannot be avoided, our framework allows us to find "least-intrusive" trajectories, measured in terms of penetration. We demonstrate the efficacy of our framework on an automated parking problem, where our numerical experiments suggest that the proposed method is robust and enables real-time optimization-based trajectory planning in tight environments. Sample code of our example is provided at https://github.com/XiaojingGeorgeZhang/OBCA .
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